Microsoft Research Podcast

College freshman Dexter Greene and Microsoft research manager Richard Black discuss how technology that stores data in glass is supporting students as they expand earlier efforts to communicate what it means to be human to extraterrestrials.

Learn more:

• Avenues: The World School — Golden Record 2.0
• Project homepage
• Golden Record: Overview
• NASA Science
• Project Silica
• Project homepage
• Sealed in glass
• Microsoft Unlocked innovation story, 2023
• Optics for the cloud: storage in the zettabyte era with Dr. Ant Rowstron and Mark Russinovich
• Microsoft Research Podcast, November 2019
• Project Silica proof of concept stores Warner Bros. ‘Superman’ movie on quartz glass
• Microsoft Source blog, November 2019

Model maker and fabricator Lex Story helps bring research to life through prototyping. He discusses his take on failure; the encouragement and advice that has supported his pursuit of art and science; and the sabbatical that might inspire his next career move.

Learn more:

• Microsoft Premonition
• Project Eclipse
• Project PRISM
• 3D Telemedicine
• Jacdac
• Audio Devices

In this episode, Microsoft Product Manager Shrey Jain and OpenAI Research Scientist Zoë Hitzig join host Amber Tingle to discuss “Personhood credentials: Artificial intelligence and the value of privacy-preserving tools to distinguish who is real online.” In their paper, Jain, Hitzig, and their coauthors describe how malicious actors can draw on increasingly advanced AI tools to carry out deception, making online deception harder to detect and more harmful. Bringing ideas from cryptography into AI policy conversations, they identify a possible mitigation: a credential that allows its holder to prove they’re a person––not a bot––without sharing any identifying information. This exploratory research reflects a broad range of collaborators from across industry, academia, and the civil sector specializing in areas such as security, digital identity, advocacy, and policy.

Researcher Brendan Lucier and professor Mert Demirer are applying their micro- and macroeconomic expertise, respectively, to forecasting the economic impact of AI. They share how they’re using a task-level breakdown of occupations to help predict the future.

Learn more:

• AI, Cognition, and the Economy (AICE) | Initiative page
• Ideas: Designing AI for people with Abigail Sellen | Microsoft Research Podcast, May 2024

Emre Kiciman shares how some keen observations and a desire to have front-end impact led him to make the jump from systems and networking to computational social science and now causal analysis and large-scale AI—and how systems thinking still impacts his work.

Learn more:

• AI Controller Interface: Generative AI with a lightweight, LLM-integrated VM (blog)
• AICI: Prompts as (Wasm) Programs (GitHub)

A lack of appropriate data, decreased model performance, and other obstacles have made it difficult to expand the input language models can receive. Li Lyna Zhang introduces LongRoPE, a method capable of extending content windows to more than 2 million tokens.

Read the paper

Get the code

Senior Researcher Arindam Mitra introduces AgentInstruct. Using raw data sources, the automated multi-agent framework can create diverse, high-quality synthetic data at scale for the post-training of small and large language models.

Read the paper

Printed circuit boards are abundant—in the stuff we use and in landfills. Researcher Jake Smith and professor Aniruddh Vashisth discuss the development of vitrimer-based PCBs that perform comparably to traditional PCBs but have less environmental impact.

Learn more:

• Recyclable vitrimer-based printed circuit boards for sustainable electronics | Nature Sustainability, April 2024
• Microsoft Climate Research Initiative
• Microsoft Research AI for Science
• Storing digital data in synthetic DNA with Dr. Karin Strauss | Microsoft Research Podcast, October 2018

Behnaz Arzani loves hard problems and the freedom to explore. That makes research a great fit! She discusses her work in network management, including the potential role of LLMs in the field; the challenges that excite her; and how storytelling changed her life.

Learn more:

• Solving Max-Min Fair Resource Allocations Quickly on Large Graphs | Publication, February 2024
• Finding Adversarial Inputs for Heuristics using Multi-level Optimization | Publication, February 2024
• MetaOpt: Examining, explaining, and improving heuristic performance | Microsoft Research blog, January 2024
• A Holistic View of AI-driven Network Incident Management | Publication, October 2023
• Behnaz Arzani: Painting, storytelling, and other hobbies | Microsoft Research bio page

Principal PM Manager Weishung Liu shares how a career delivering products and customer experiences aligns with her love of people and storytelling and how—despite efforts to defy the expectations that come with growing up in Silicon Valley—she landed in tech.

Learn more:

• Weishung Liu at Microsoft Research
• Watch For | Project page
• Developer Tech Minutes: Watch For | Video, 2021

Social scientist and HCI expert Abigail Sellen explores the critical understanding needed to build human-centric AI through the lens of the new AICE initiative, a collective of interdisciplinary researchers studying AI impact on human cognition and the economy.

Learn more:

• AI, Cognition, and the Economy (AICE) 
• Responsible AI Principles and Approach | Microsoft AI  
• The Rise of the AI Co-Pilot: Lessons for Design from Aviation and Beyond 
• The Myth of the Paperless Office

Andrey Kolobov discusses WindSeer, a small CNN capable of estimating the wind field around an sUAV in flight more finely and with less compute and data than traditional models. The advancement can help support longer and safer autonomous flights.

Learn more:

• WindSeer: Real-time volumetric wind prediction over complex terrain aboard a small uncrewed aerial vehicle

Jacki O'Neill saw an opportunity to expand Microsoft research efforts to Africa. She now leads Microsoft Research Africa, Nairobi (formerly MARI). O'Neill talks about the choices that got her there, the lab’s impact, and how living abroad is good for innovation. 

Learn more:

• Jacki O'Neill at Microsoft Research
• Microsoft Research Africa (formerly MARI)

Researcher Michel Galley explores how he and fellow researchers combined new and existing data to create MathVista, an open-source benchmark for measuring the mathematical reasoning capabilities of foundation models in scenarios that involve text and images.

Read the paper

Get the code & dataset

Energized by disruption, partner group product manager Rafah Hosn is helping to drive scientific advancement in AI for Microsoft. She talks about the mindset needed to work at the frontiers of AI and how the research-to-product pipeline is changing in the GenAI era.

Learn more:

• AI Frontiers - Microsoft Research
• Responsible AI Principles and Approach | Microsoft AI

Tusher Chakraborty talks about the paper “Spectrumize: Spectrum-efficient Satellite Networks for the Internet of Things,” including a method for supporting communication between a large IoT-satellite constellation and devices on Earth within a limited spectrum.

Read the paper

The new series “Ideas” debuts with guest Kalika Bali. The speech and language tech researcher talks sci-fi and its impact on her career, the design thinking philosophy behind her research, and the “outrageous idea” she had to work with low-resource languages. 

Learn more:

• The State and Fate of Linguistic Diversity and Inclusion in the NLP World | Publication, July 2020
• Project VeLLM | Project page
• Kahani: Visual Storytelling | Project page
• Kahani: Visual Storytelling through Culturally Nuanced Images | Microsoft Research Forum | Episode 1, January 2024
• Teachers in India help Microsoft Research design AI tool for creating great classroom content | Microsoft Research blog, October 2023
• Digital Labor: Project Karya | Project page
• Village by village, creating the building blocks for AI tools with work that also educates | Microsoft Source Asia blog, February 2024

Principal Researcher Ida Momennejad brings her expertise in cognitive neuroscience and computer science to this in-depth conversation about general intelligence and what the evolution of the brain across species can teach us about building AI.

Learn more:

• AI and Microsoft Research | Focus Area
• Evaluating Cognitive Maps and Planning in Large Language Models with CogEval | Publication, October 2023
• Imitating Human Behaviour with Diffusion Models | Publication, May 2023
• Navigates Like Me: Understanding How People Evaluate Human-Like AI in Video Games | Publication, April 2023
• Navigation Turing Test (NTT): Learning to Evaluate Human-Like Navigation | Publication, July 2021
• Predictive Representations in Hippocampal and Prefrontal Hierarchies | Publication, January 2022
• The successor representation in human reinforcement learning | Publication, September 2017
• Encoding of Prospective Tasks in the Human Prefrontal Cortex under Varying Task Loads | Publication, October 2013

Senior Researcher Chang Liu discusses M-OFDFT, a variation of orbital-free density functional theory (OFDFT) that leverages deep learning to help identify molecular properties in a way that minimizes the tradeoff between accuracy and efficiency. 

Read the paper

Can how we think about our thinking help us better incorporate generative AI in our lives & work? Explore metacognition’s potential to improve the tech’s usability on “Abstracts,” then sign up for Microsoft Research Forum for more on this & other AI work.

Read the paper

Partner Research Manager and developer experience expert Nicole Forsgren talks about the future of software engineering with AI, why she loves tech, and her reliance on a spreadsheet and her gut when making career-changing decisions.

Learn more:

• Nicole Forsgren at Microsoft Research
• Nicole Forsgren website
• Quantifying the impact of developer experience | Microsoft Azure Blog, January 2024
• Yes, good DevEx increases productivity. Here is the data. | GitHub blog, January 2024
• Accelerate: The Science of Lean Software and DevOps: Building and Scaling High Performing Technology Organizations | Book, 2018

Partner Software Architect Ivan Tashev talks about applying his expertise in audio signal processing to the design and study of audio components for Microsoft products such as Kinect and shares how a focus on what he can control has fueled professional success.

Learn more:

• Ivan Tashev at Microsoft Research
• Distributed Meetings: A Meeting Capture and Broadcasting System | Publication, December 2002
• Research Collection: The Unseen History of Audio and Acoustics Research at Microsoft | Microsoft Research blog, August 2020 

On “Abstracts,” Jordan Ash & Dipendra Misra discuss the parameter reduction method LASER. Tune in to learn how selective removal of stored data alone can boost LLM performance, then sign up for Microsoft Research Forum for more on LASER & related topics.

Learn more:

• The Truth is in There: Improving Reasoning in Language Models with Layer-Selective Rank Reduction | Publication, December 2023
• LASER code on GitHub

Powerful large-scale AI models like GPT-4 are showing dramatic improvements in reasoning, problem-solving, and language capabilities. This marks a phase change for artificial intelligence—and a signal of accelerating progress to come.

In this Microsoft Research Podcast series, AI scientist and engineer Ashley Llorens hosts conversations with his collaborators and colleagues about what these models—and the models that will come next—mean for our approach to creating, understanding, and deploying AI, its applications in areas such as healthcare and education, and its potential to benefit humanity.

This episode features Technical Fellow Christopher Bishop, who leads a global team of researchers and engineers working to help accelerate scientific discovery by merging machine learning and the natural sciences. Llorens and Bishop explore the state of deep learning; Bishop’s new textbook Deep Learning: Foundations and Concepts, his third and a writing collaboration with his son; and a potential future in which “super copilots” accessible via natural language and drawing on a variety of tools, like those that can simulate the fundamental equations of nature, are empowering scientists in their pursuit of breakthrough.

Learn more:

• Deep Learning: Foundations and Concepts | Textbook, 2023
• Pattern Recognition and Machine Learning | Textbook, 2006
• Neural Networks for Pattern Recognition | Textbook, 1995

Members of the research community at Microsoft work continuously to advance their respective fields. Abstracts brings its audience to the cutting edge with them through short, compelling conversations about new and noteworthy achievements. 

In this episode, Senior Principal Research Manager Tao Qin and Senior Researcher Lijun Wu discuss “FABind: Fast and Accurate Protein-Ligand Binding.” The paper, accepted at the 2023 Conference on Neural Information Processing Systems (NeurIPS), introduces a new method for predicting the binding structures of proteins and ligands during drug development. The method demonstrates improved speed and accuracy over current methods.

Learn more:

• FABind: Fast and Accurate Protein-Ligand Binding
• FABind code on GitHub

Members of the research community at Microsoft work continuously to advance their respective fields. Abstracts brings its audience to the cutting edge with them through short, compelling conversations about new and noteworthy achievements.

In this episode, Principal Researcher Alessandro Sordoni joins host Gretchen Huizinga to discuss “Joint Prompt Optimization of Stacked LLMs using Variational Inference.” In the paper, which was accepted at the 2023 Conference on Neural Information Processing Systems (NeurIPS), Sordoni and his coauthors introduce Deep Language Networks, or DLNs, an architecture that treats large language models as layers within a network and natural language prompts as each layer’s learnable parameters.

Read the paper

Members of the research community at Microsoft work continuously to advance their respective fields. Abstracts brings its audience to the cutting edge with them through short, compelling conversations about new and noteworthy achievements.

In this episode, Xing Xie, a Senior Principal Research Manager of Microsoft Research Asia, joins host Dr. Gretchen Huizinga to discuss “Evaluating General-Purpose AI with Psychometrics.” As AI capabilities move from task specific to more general purpose, the paper explores psychometrics, a subfield of psychology, as an alternative to traditional methods for evaluating model performance and for supporting consistent and reliable systems.

Read the paper: Evaluating General-Purpose AI with Psychometrics

Transforming research ideas into meaningful impact is no small feat. It often requires the knowledge and experience of individuals from across disciplines and institutions. Collaborators, a Microsoft Research Podcast series, explores the relationships—both expected and unexpected—behind the projects, products, and services being pursued and delivered by researchers at Microsoft and the diverse range of people they’re teaming up with.

In this episode, Dr. Gretchen Huizinga speaks with Cecily Morrison, MBE, a Senior Principal Research Manager at Microsoft Research, and Karolina Pakėnaitė, who also goes by Caroline, a PhD student and member of the citizen design team working with Morrison on the research project Find My Things. An AI phone application designed to help people who are blind or have low vision locate their personal items, Find My Things is an example of a broader research approach known as Teachable AI. Morrison and Pakėnaitė explore the Teachable AI goal of empowering people to make an AI experience work for them. They also discuss how “designing for one” when it comes to inclusive design leads to innovative solutions and what they learned about optimizing these types of systems for real-world use (spoiler: it’s not necessarily more or higher-quality data).

Learn more:

• Teachable AI Experiences (Tai X) | Project page
• Understanding Personalized Accessibility through Teachable AI: Designing and Evaluating Find My Things for People who are Blind or Low Vision | Publication, October 2023
• Microsoft Inclusive Design | Inclusive design resource center
• DeafBlind Everest Project | Karolina (Caroline) Pakėnaitė personal website

Members of the research community at Microsoft work continuously to advance their respective fields. Abstracts brings its audience to the cutting edge with them through short, compelling conversations about new and noteworthy achievements.

In this episode, Shrey Jain, a Technical Project Manager at Microsoft Research, and Dr. Zoë Hitzig, a junior fellow at the Harvard Society of Fellows, discuss their work on contextual confidence, which presents a framework to understand and more meaningfully address the increasingly sophisticated challenges generative AI poses to communication.

Read the paper

In this new Microsoft Research Podcast series What’s Your Story, Johannes Gehrke explores the who behind the technical and scientific advancements helping to reshape the world. A systems expert whose 10 years with Microsoft spans research and product, Gehrke talks to members of the company’s research community about what motivates their work and how they got where they are today.

Across his time at Microsoft, Desney Tan, Managing Director of Microsoft Research Redmond, has had the experience of shepherding research ideas into products multiple times, and much like the trajectory of research, his life journey has been far from linear. In this episode, Tan shares how he moved to the United States from Singapore as a teenager, how his self-described “brashness” as a Microsoft intern helped shift the course of his career, and how human impact has been a guiding force in his work.

Members of the research community at Microsoft work continuously to advance their respective fields. Abstracts brings its audience to the cutting edge with them through short, compelling conversations about new and noteworthy achievements.

In this episode, Andy Gordon, a Partner Research Manager, and Carina Negreanu, a Senior Researcher, both at Microsoft Research, join host Dr. Gretchen Huizinga to discuss “Co-audit: Tools to help humans double-check AI-generated content.” This paper brings together current understanding of generative AI performance to explore the need and context for tools to help people using the technology find and fix mistakes in AI output.

View the paper

In this new Microsoft Research Podcast series What’s Your Story, Lab Director Johannes Gehrke explores the who behind the technical and scientific advancements helping to reshape the world. He talks to members of the research community at Microsoft about what motivates their work and how they got where they are today.

Ranveer Chandra is Managing Director of Research for Industry and CTO of Agri-Food. He is also Head of Networking Research at Microsoft Research Redmond. His work in systems and networking is helping to bring more internet connectivity to more people and is yielding tools designed to help farmers increase food production more affordably and sustainably. In this episode, he shares what it was like growing up in Jamshedpur, India; why he focuses his efforts in the areas he does; and where the joy in his work comes from.

Learn more:

• Ranveer Chandra at Microsoft Research
• FarmBeats: AI, Edge & IoT for Agriculture
• Project FarmVibes
• 6G | Space

Members of the research community at Microsoft work continuously to advance their respective fields. Abstracts brings its audience to the cutting edge with them through short, compelling conversations about new and noteworthy achievements. 

In this episode, Dr. Sheng Zhang, a Senior Researcher at Microsoft Research, joins host Dr. Gretchen Huizinga to discuss “UniversalNER: Targeted Distillation from Large Language Models for Open Named Entity Recognition.” In this paper, Zhang and his coauthors present mission-focused instruction tuning, a method for distilling large language models into smaller, more efficient ones for a broad application class. Their UniversalNER models achieved state-of-the-art performance in named entity recognition, an important natural language processing (NLP) task. Model distillation has the potential to make NLP and other capabilities more accessible, particularly in specialized domains such as biomedicine, which could benefit from more resource-efficient and transparent options. 

Learn more:

• View the paper
• UniversalNER project website with demo
• Code on GitHub
• Dataset and models on Hugging Face

Every year, interns from academic institutions around the world apply and grow their knowledge as members of the research community at Microsoft. In this Microsoft Research Podcast series, these students join their internship supervisors to share their experience working alongside some of the leading researchers in their respective fields. 

In this episode, PhD students Jennifer Scurrell and Alejandro Cuevas talk to Senior Researcher Dr. Madeleine Daepp. They discuss the internship culture at Microsoft Research, from opportunities to connect with researchers they admire over coffee to the teamwork they say helped make it possible for them to succeed in the fast-paced environment of industry, and the impact they hope to have with their work. 

Learn more:

• Automated Interviewer or Augmented Survey? Collecting Social Data with Large Language Models | Publication, September 2023 

Powerful large-scale AI models like GPT-4 are showing dramatic improvements in reasoning, problem-solving, and language capabilities. This marks a phase change for artificial intelligence—and a signal of accelerating progress to come.

In this Microsoft Research Podcast series, AI scientist and engineer Ashley Llorens hosts conversations with his collaborators and colleagues about what these models—and the models that will come next—mean for our approach to creating, understanding, and deploying AI, its applications in areas such as healthcare and education, and its potential to benefit humanity.

This episode features Partner Research Manager Hanna Wallach, whose research into fairness, accountability, transparency, and ethics in AI and machine learning has helped inform the use of AI in Microsoft products and services for years. Wallach describes how she and a team of applied scientists expanded their tools for measuring fairness-related harms in AI systems to address harmful content more broadly during their involvement in the deployment of Bing Chat; her interest in filtering, a technique for mitigating harms that she describes as widely used but not often talked about; and the cross-company collaboration that brings policy, engineering, and research together to evolve and execute the Microsoft approach to developing and deploying AI responsibly.

Learn more: 

Microsoft AI: Responsible AI Principles and Approach  

AI and Microsoft Research 

Powerful large-scale AI models like GPT-4 are showing dramatic improvements in reasoning, problem-solving, and language capabilities. This marks a phase change for artificial intelligence—and a signal of accelerating progress to come.  

In this Microsoft Research Podcast series, AI scientist and engineer Ashley Llorens hosts conversations with his collaborators and colleagues about what these models—and the models that will come next—mean for our approach to creating, understanding, and deploying AI, its applications in areas such as healthcare and education, and its potential to benefit humanity.

This episode features Senior Principal Research Manager Ahmed H. Awadallah, whose work improving the efficiency of large-scale AI models and efforts to help move advancements in the space from research to practice have put him at the forefront of this new era of AI. Awadallah discusses the shift in dynamics between model size and amount—and quality—of data when it comes to model training; the recently published paper “Orca: Progressive Learning from Complex Explanation Traces of GPT-4,” which further explores the use of large-scale AI models to improve the performance of smaller, less powerful ones; and the need for better evaluation strategies, particularly as we move into a future in which Awadallah hopes to see gains in these models’ ability to continually learn.

Learn more:

• Orca: Progressive Learning from Complex Explanation Traces of GPT-4, June 2023 
• Textbooks Are All You Need II: phi-1.5 technical report, September 2023
• AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation Framework, August 2023 
• LIDA: Automatic Generation of Grammar-Agnostic Visualizations and Infographics using Large Language Models, March 2023
• AI Explainer: Foundation models ​and the next era of AI, March 2023 
• AI and Microsoft Research

Members of the research community at Microsoft work continuously to advance their respective fields. Abstracts brings its audience to the cutting edge with them through short, compelling conversations about new and noteworthy achievements.

In the inaugural episode of the series, Dr. Ava Amini and Dr. Kevin K. Yang, both Senior Researchers with Microsoft Health Futures, join host Dr. Gretchen Huizinga to discuss “Protein generation with evolutionary diffusion: Sequence is all you need.” The paper introduces EvoDiff, a suite of models that leverages evolutionary-scale protein data to help design novel proteins more efficiently. Improved protein engineering has the potential to help create new vaccines to prevent disease and new ways to recycle plastics.

Every year, interns from academic institutions around the world apply and grow their knowledge as members of the research community at Microsoft. In this Microsoft Research Podcast series, these students join their internship supervisors to share their experience working alongside some of the leading researchers in their respective fields.

In this episode, PhD students Anunay Kulshrestha and Karan Newatia talk to Senior Cryptographer Josh Benaloh about their work this summer on ElectionGuard, a free, open-source toolkit that enables voters to verify that their votes have been accurately counted. Kulshrestha and Newatia discuss their contributions to extending ElectionGuard to mail-in voting and rank-choice voting, respectively; what is needed for widespread adoption of the verifiable election technology; and why they’d recommend a Microsoft internship to other students.

(Editor’s note: After its design and development by Microsoft, ElectionGuard is now part of the newly formed nonprofit Election Technology Initiative, which will join with Microsoft to further ElectionGuard’s growth and help advance its adoption.)

Learn more

• ElectionGuard | Project page
• The next frontier in elections: Microsoft supports the Council of State Governments’ Election Technology Initiative | Microsoft On the Issues blog, July 2023
• Security and Cryptography | Group page

Powerful large-scale AI models like GPT-4 are showing dramatic improvements in reasoning, problem-solving, and language capabilities. This marks a phase change for artificial intelligence—and a signal of accelerating progress to come. 

In this Microsoft Research Podcast series, AI scientist and engineer Ashley Llorens hosts conversations with his collaborators and colleagues about what these models—and the models that will come next—mean for our approach to creating, understanding, and deploying AI, its applications in areas such as healthcare and education, and its potential to benefit humanity.

This episode features Sriram Rajamani, Distinguished Scientist and Managing Director of Microsoft Research India. Rajamani talks about how the lab’s work is being influenced by today’s rapidly advancing AI. One example? The development of a conversational agent in India capable of providing information about governmental agricultural programs in farmers’ natural language, particularly significant in a country with more than 30 languages, including 22 government-recognized languages. It’s an application Microsoft CEO Satya Nadella described as the “mic drop moment” of his trip to the lab early this year.

Learn more

• AI4Bhārat | Organization homepage
• MEGA: Multilingual Evaluation of Generative AI | Publication, May 2023
• AI and Microsoft Research | Learn more about the breadth of AI research at Microsoft

Transforming research ideas into meaningful impact is no small feat. It often requires the knowledge and experience of individuals from across disciplines and institutions. Collaborators, a new Microsoft Research Podcast series, explores the relationships—both expected and unexpected—behind the projects, products, and services being pursued and delivered by researchers at Microsoft and the diverse range of people they’re teaming up with.

In this episode, Dr. Gretchen Huizinga talks with Microsoft Health Futures Senior Director Javier Alvarez and Dr. Raj Jena, a radiation oncologist at Addenbrooke’s hospital, part of Cambridge University Hospitals in the United Kingdom, about Project InnerEye, a Microsoft Research effort that applies machine learning to medical image analysis. The pair shares how a 10-plus-year collaborative journey—and a combination of research and good software engineering—has resulted in the hospital’s creation of an AI system that is helping to decrease the time cancer patients have to wait to begin treatment. Alvarez and Jena chart the path of their collaboration in AI-assisted medical imaging, from Microsoft Research’s initiation of Project InnerEye and its decision to make the resulting research tools available in open source to Addenbrooke’s subsequent testing and validation of these tools to meet the regulatory requirements for use in a clinical setting. They also discuss supporting clinician productivity—and ultimately patient outcomes—and the important role patients play in incorporating AI into healthcare.

Learn more:

• Project InnerEye | Project page
• How AI is helping to shrink waiting times for NHS cancer patients | Microsoft News Centre UK blog post, June 2023
• Accounting for past imaging studies: Enhancing radiology AI and reporting | Microsoft Research blog, June 2023
• Microsoft Health Futures | Lab page
• Biomedical Imaging | Research group page
• Evaluation of Deep Learning to Augment Image Guided Radiotherapy for Head and Neck and Prostate Cancers | JAMA publication, November 2020

Transforming research ideas into meaningful impact is no small feat. It often requires the knowledge and experience of individuals from across disciplines and institutions. Collaborators, a new Microsoft Research Podcast series, explores the relationships—both expected and unexpected—behind the projects, products, and services being pursued and delivered by researchers at Microsoft and the diverse range of people they’re teaming up with.

In this episode of the podcast, Dr. Gretchen Huizinga welcomes Principal Researcher Dr. Jina Suh and Principal Applied and Data Science Manager Dr. Shamsi Iqbal to the show to discuss their most recent work together, a research project aimed at developing data-driven tools to support organizational leaders and executives in their decision-making. The longtime collaborators explore how a long history of collaboration helps them thrive in their work to help workplaces thrive, how their relationship has evolved over the years, particularly with Iqbal’s move from the research side to the product side, and how research and product can align to achieve impact.

Learn more:

• HUE: Human Understanding and Empathy | Project page
• Microsoft Viva | Product page

Transforming research ideas into meaningful impact is no small feat. It often requires the knowledge and experience of individuals from across disciplines and institutions. Collaborators, a new Microsoft Research Podcast series, explores the relationships—both expected and unexpected—behind the projects, products, and services being pursued and delivered by researchers at Microsoft and the diverse range of people they’re teaming up with.

In the world of gaming, Haiyan Zhang has situated herself where research meets real-world challenges, helping to bring product teams and researchers together to elevate the player experience with the latest AI advances even before the job became official with the creation of her current role, General Manager of Gaming AI. In this episode, she talks with host Dr. Gretchen Huizinga about the variety of expertise needed to avoid the discomfort experienced by players when they encounter a humanlike character displaying inhuman behavior, the potential for generative AI to make gaming better for both players and creators, and the games she grew up playing and what she plays now.

Learn more:

• Game Intelligence | Group page
• Project Paidia | Project page
• TrueSkill™ Ranking System | Project page
• TrueMatch Matchmaking System | Project page
• Grounded Conversational Characters | Project page

Transforming research ideas into meaningful impact is no small feat. It often requires the knowledge and experience of individuals from across disciplines and institutions. Collaborators, a new Microsoft Research Podcast series, explores the relationships—both expected and unexpected—behind the projects, products, and services being pursued and delivered by researchers at Microsoft and the diverse range of people they’re teaming up with.

In this episode, host Dr. Gretchen Huizinga welcomes Dr. Spencer Fowers, a member of the Special Projects Technical Staff at Microsoft Research, and Dr. Kwame Darko, a plastic surgeon in the reconstructive plastic surgery and burns center in Ghana’s Korle Bu Teaching Hospital. The two are among a group working to make specialized medical care more widely available, especially to those in remote or underserved communities. They share how their 3D telecommunication technology helps bring patients and doctors together when being in the same room isn’t an easy option and how the experience is supporting greater patient satisfaction, allowing more time for surgeons to prepare for surgery, and making the assembly of a super team of medical experts from around the globe more feasible.

Learn more:

• 3D telemedicine brings better care to underserved and rural communities, even across continents | Microsoft Research Blog, May 2023
• Microsoft’s Holoportation Communications Technology: Facilitating 3D Telemedicine | Microsoft Research video, May 2023
• Participatory Development of a 3D Telemedicine system during Covid: the future of remote consultations | Journal of Plastic, Reconstructive & Aesthetic Surgery, October 2022
• 3D Telemedicine | Project page
• Holoportation | Project page
• Korle Bu Teaching Hospital

Transforming research ideas into meaningful impact is no small feat. It often requires the knowledge and experience of individuals from across disciplines and institutions. Collaborators, a new Microsoft Research Podcast series, explores the relationships—both expected and unexpected—behind the projects, products, and services being pursued and delivered by researchers at Microsoft and the diverse range of people they’re teaming up with.

In this episode, Microsoft Principal Researcher Dr. Bichlien Nguyen and Dr. David Kwabi, Assistant Professor of Mechanical Engineering at the University of Michigan, join host Dr. Gretchen Huizinga to talk about how their respective research interests—and those of their larger teams—are converging to develop renewable energy storage systems. They specifically explore their work in flow batteries and how machine learning can help more effectively search the vast organic chemistry space to identify compounds with properties just right for storing waterpower and other renewables for a not rainy day. The bonus? These new compounds may just help advance carbon capture, too.

Learn more

• Microsoft Climate Research Initiative
• Project Zerix
• Project Carbonix
• Kwabi Lab, University of Michigan
• Understanding capacity fade in organic redox-flow batteries by combining spectroscopy with statistical inference techniques

Powerful new large-scale AI models like GPT-4 are showing dramatic improvements in reasoning, problem-solving, and language capabilities. This marks a phase change for artificial intelligence—and a signal of accelerating progress to come.

In this Microsoft Research Podcast series, AI scientist and engineer Ashley Llorens hosts conversations with his collaborators and colleagues about what these new models—and the models that will come next—mean for our approach to creating, understanding, and deploying AI, its applications in areas such as health care and education, and its potential to benefit humanity.

This episode features Senior Principal Researcher Emre Kiciman and Principal Researcher Amit Sharma, whose paper “Causal Reasoning and Large Language Models: Opening a New Frontier for Causality” examines the causal capabilities of large language models (LLMs) and their implications. Kiciman and Sharma break down the study of cause and effect; recount their respective ongoing journeys with GPT-3.5 and GPT-4—from their preconceptions to where they are now—and share their views of a future in which LLMs help bring together different modes of reasoning in the practice of causal inference and make causal methods easier to adopt.

Learn more

• Causal Reasoning and Large Language Models: Opening a New Frontier for Causality | Publication, April 2023
• The AI Revolution in Medicine: GPT-4 and Beyond | Book by Peter Lee, April 2023
• AI and Microsoft Research | Learn more about the breadth of AI research at Microsoft

Transforming research ideas into meaningful impact is no small feat. It often requires the knowledge and experience of individuals from across disciplines and institutions. Collaborators, a new Microsoft Research podcast series, explores the relationships—both expected and unexpected—behind the projects, products, and services being pursued and delivered by researchers at Microsoft and the diverse range of people they're teaming up with. 

In this inaugural episode, host Dr. Gretchen Huizinga talks with GitHub Staff Product Manager Kasia Sitkiewicz and Protocol Labs Research Scientist Petar Maymounkov about how their collaboration on Gov4git, a governance tool for decentralized, open-source cooperation, is helping to lay the foundation for a future in which everyone can collaborate more efficiently, transparently, and easily and in the ways that meet the unique desires and needs of their respective communities. They discuss the governance features that make Gov4git more suitable for serving a broader range of communities than today’s public blockchains and the open-source book project allowing them to test the potential and limitations of the work.

https://www.microsoft.com/research

Powerful new large-scale AI models like GPT-4 are showing dramatic improvements in reasoning, problem-solving, and language capabilities. This marks a phase change for artificial intelligence—and a signal of accelerating progress to come.

In this Microsoft Research Podcast series, AI scientist and engineer Ashley Llorens hosts conversations with his collaborators and colleagues about what these new models—and the models that will come next—mean for our approach to creating, understanding, and deploying AI, its applications in areas such as health care and education, and its potential to benefit humanity.

The third episode features Ece Kamar, deputy lab director at Microsoft Research Redmond. Kamar draws on decades of experience in AI research and an opportunity she and Microsoft colleagues had to evaluate and experiment with GPT-4 prior to its release in discussing the capabilities and limitations of today’s large-scale models. She explores the short-term mitigation techniques she and her team are using to make these models viable components of the AI systems that give them purpose and shares the long-term research questions that will help maximize their value. 

https://www.microsoft.com/research

Powerful new large-scale AI models like GPT-4 are showing dramatic improvements in reasoning, problem-solving, and language capabilities. This marks a phase change for artificial intelligence—and a signal of accelerating progress to come.

In this new Microsoft Research Podcast series, AI scientist and engineer Ashley Llorens hosts conversations with his collaborators and colleagues about what these new models—and the models that will come next—mean for our approach to creating, understanding, and deploying AI, its applications in areas such as health care and education, and its potential to benefit humanity.

The second episode features Peter Lee, head of Microsoft Research. Lee was among a group within Microsoft to have early access to GPT-4 for evaluation and experimentation. Here, he applies his philosophy of tackling research from what will be inevitably true at a future point in time to this current moment. He also explores the differences that may make integrating today’s AI advancements into health care more attainable, a topic he expands on in the soon-to-be-released book The AI Revolution in Medicine: GPT-4 and Beyond and the New England Journal of Medicine article "Benefits, Limits, and Risks of GPT-4 as an AI Chatbot for Medicine."

https://www.microsoft.com/research

Powerful new large-scale AI models like GPT-4 are showing dramatic improvements in reasoning, problem-solving, and language capabilities. This marks a phase change for artificial intelligence—and a signal of accelerating progress to come.

In this new Microsoft Research Podcast series, AI scientist and engineer Ashley Llorens hosts conversations with his collaborators and colleagues about what these new models—and the models that will come next—mean for our approach to creating, understanding, and deploying AI, its applications in areas such as health care and education, and its potential to benefit humanity.

The first episode features Sébastien Bubeck, who leads the Machine Learning Foundations group at Microsoft Research in Redmond. He and his collaborators conducted an extensive evaluation of GPT-4 while it was in development, and have published their findings in a paper that explores its capabilities and limitations—noting that it shows “sparks” of artificial general intelligence.

https://www.microsoft.com/research

Transforming research ideas into meaningful impact is no small feat. It often requires the knowledge and experience of individuals from across disciplines and institutions. Collaborators, a new Microsoft Research Podcast series, explores the relationships—both expected and unexpected—behind the projects, products, and services being pursued and delivered by researchers at Microsoft and the diverse range of people they’re teaming up with.

In the world of gaming, Haiyan Zhang has situated herself where research meets real-world challenges, helping to bring product teams and researchers together to elevate the player experience with the latest AI advances even before the job became official with the creation of her current role, General Manager of Gaming AI. In this episode, she talks with host Dr. Gretchen Huizinga about the variety of expertise needed to avoid the discomfort experienced by players when they encounter a humanlike character displaying inhuman behavior, the potential for generative AI to make gaming better for both players and creators, and the games she grew up playing and what she plays now.

Learn more

• Game Intelligence | Group page
• Project Paidia | Project page
• TrueSkill™ Ranking System | Project page
• TrueMatch Matchmaking System | Project page
• Grounded Conversational Characters | Project page

In “Just Tech: Centering Community-Driven Innovation at the Margins,” Senior Principal Researcher Mary L. Gray explores how technology and community intertwine and the role technology can play in supporting community-driven innovation and community-based organizations. Dr. Gray and her team are working to bring computer science, engineering, social science, and communities together to boost societal resilience in ongoing work with Project Resolve. She’ll talk with organizers, academics, technology leaders, and activists to understand how to develop tools and frameworks of support alongside members of these communities.    

In this episode of the series, Dr. Gray and Dr. Sasha Costanza-Chock, scholar, designer, and activist, explore design justice, a framework for analyzing design’s power to perpetuate—or take down—structural inequality and a community of practice dedicated to creating a more equitable and sustainable world through inclusive, thoughtful, and respectful design processes. They also discuss how critical thinkers and makers from social movements have influenced technology design and science and technology studies (STS), how challenging the assumptions that drive who tech is built for will create better experiences for most of the planet, and how a deck of tarot-inspired cards is encouraging radically wonderful sociotechnical futures.

https://www.microsoft.com/research

In “Just Tech: Centering Community-Driven Innovation at the Margins,” Senior Principal Researcher Mary Gray explores how technology and community intertwine and the role technology can play in supporting community-driven innovation and community-based organizations. Dr. Gray and her team are working to bring computer science, engineering, social science, and community together to boost societal resilience in ongoing work with Project Resolve. She’ll talk with organizers, academics, technology leaders, and activists to understand how to develop tools and frameworks of support alongside members of these communities. In this episode of the series, Dr. Gray talks with Dr. Tawanna Dillahunt, Associate Professor at University of Michigan’s School of Information, Zachary Rowe, Executive Director of Friends of Parkside, and Joanna Velazquez, Campaign Manager at Detroit Action. The guests share personal experiences where community and research collaborations have been most impactful in solving problems, talk about ways that participatory research can foster equal partnerships and fuel innovation, and offer perspectives on how researchers can best work with communities to work through problems at a local level. They also discuss the role that technology plays—and doesn’t play—in their work.

https://www.microsoft.com/research

In “Just Tech: Centering Community-Driven Innovation at the Margins,” Senior Principal Researcher Mary Gray explores how technology and community intertwine and the role technology can play in supporting community-driven innovation and community-based organizations. Dr. Gray and her team are working to bring computer science, engineering, social science, and community together to boost societal resilience in ongoing work with Project Resolve. She’ll talk with organizers, academics, technology leaders, and activists to understand how to develop tools and frameworks of support alongside members of these communities. In this episode of the series, Dr. Gray talks with Dr. Desmond Patton, whose work at the intersection of social work, social media, and technology seeks to understand the root of aggression, grief, and trauma in ways that can help inform interventions for social workers and broader communities. Together, they explore Patton’s learnings about the challenges of using AI in a field that’s full of nuance and how informed technology can make positive social impacts in partnership with local communities. Dr. Patton also shares how his work on gang violence has grown his understanding of how social media can influence and transform the narratives about people.

https://www.microsoft.com/research

For Microsoft researchers, COVID-19 was a call to action. The reimagining of work practices had long been an area of study, but existing and new questions that needed immediate answers surfaced as companies and their employees quickly adjusted to significantly different working conditions. Teams from across the Microsoft organizational chart pooled their unique expertise together under The New Future of Work initiative. The results have informed product features designed to better support remote work and are now being used to help companies, including Microsoft, usher their workforces into a future of hybrid work.

In this episode of The New Future of Work series, Chief Scientist Jaime Teevan and Senior Principal Researcher Siddharth Suri explore the many ways people were impacted by work shifts during the COVID-19 pandemic. They talk about how race, gender, income, and other factors are indicative of how people have fared and what this means for the future of work. The researchers discuss the importance of examining potential hidden consequences—and patience—when using short-term data to make long-term decisions, emphasizing aspects of burnout and innovation. Topics covered in this wide-ranging conversation include benefits of commutes and a silver lining in the shift to remote and hybrid work—the movement of more innovative jobs out of large metro areas, creating momentum for greater opportunity in diverse locations. The research that Siddharth Suri describes in this podcast was jointly done with Hana Wolf of LinkedIn.

https://www.microsoft.com/research

For Microsoft researchers, COVID-19 was a call to action. The reimagining of work practices had long been an area of study, but existing and new questions that needed immediate answers surfaced as companies and their employees quickly adjusted to significantly different working conditions. Teams from across the Microsoft organizational chart pooled their unique expertise together under The New Future of Work initiative. The results have informed product features designed to better support remote work and are now being used to help companies, including Microsoft, usher their workforces into a future of hybrid work.

In this episode of The New Future of Work series, Chief Scientist Jaime Teevan and Principal User Research Manager Ginger Hudson share how people evolved their home office setups throughout the COVID-19 pandemic, and they explore how information workers used various devices and peripherals to put their best self forward as the shift to remote work quickly unfolded. They also talk about what an “anatomy of hybrid work” might look like and some considerations for making a hybrid model of work sustainable in the long term, including the expansion of workspaces to outdoor environments.

https://www.microsoft.com/research

For Microsoft researchers, COVID-19 was a call to action. The reimagining of work practices had long been an area of study, but existing and new questions that needed immediate answers surfaced as companies and their employees quickly adjusted to significantly different working conditions. Teams from across the Microsoft organizational chart pooled their unique expertise together under The New Future of Work initiative. The results have informed product features designed to better support remote work and are now being used to help companies, including Microsoft, usher their workforces into a future of hybrid work.

In this episode of the podcast, Chief Scientist Jaime Teevan and Senior User Research Manager Matt Brodsky examine how the level of IT support available during the shift, including the ability to provide hardware and software, made the difference between laying off staff and weathering the challenges brought on by the pandemic. They also explore why remote work came with a spike in phishing threats, what the biggest thorn in the sides of IT administrators has been this past year, and where opportunities exist to prepare to keep up with tech advances and tackle future disruptions.

https://www.microsoft.com/research

Unlocking the challenge of molecular simulation has the potential to yield significant breakthroughs in how we tackle such societal issues as climate change, drug discovery, and the treatment of disease, and Microsoft is ramping up its efforts in the space.

In this episode, Chris Bishop, Lab Director of Microsoft Research Cambridge, welcomes renowned machine learning researcher Max Welling to the Microsoft Research team as head of the new Amsterdam lab. Connecting over their shared physics background and vision for molecular simulation, Bishop and Welling explore several fascinating topics, including a future in which machine learning and quantum computing will be used in tandem to model molecules, the power of machine learning to provide “on demand” data in this space, and goals for the first year and beyond at the Amsterdam lab.

https://www.microsoft.com/research

For Microsoft researchers, COVID-19 was a call to action. The reimagining of work practices had long been an area of study, but existing and new questions that needed immediate answers surfaced as companies and their employees quickly adjusted to significantly different working conditions. Teams from across the Microsoft organizational chart pooled their unique expertise together under The New Future of Work initiative. The results have informed product features designed to better support remote work and are now being used to help companies, including Microsoft, usher their workforces into a future of hybrid work.

In this episode of The New Future of Work series, Chief Scientist Jaime Teevan and Principal Productivity Engineer Brian Houck discuss what the massive shift to remote work meant for developers—both employees of Microsoft and customers using Microsoft developer platforms to support their work. They’ll talk about how taking a holistic approach to developer productivity can benefit both efficiency and happiness, with an emphasis on the important role social connections and processes play in a field often thought of as an isolated endeavor. They also explore pros and cons of everyday developer tasks, like code review and whiteboarding, being done in a hybrid work setting.

https://www.microsoft.com/research

For Microsoft researchers, COVID-19 was a call to action. The reimagining of work practices had long been an area of study, but existing and new questions that needed immediate answers surfaced as companies and their employees quickly adjusted to significantly different working conditions. Teams from across the Microsoft organizational chart pooled their unique expertise together under The New Future of Work initiative. The results have informed product features designed to better support remote work and are now being used to help companies, including Microsoft, usher their workforces into a future of hybrid work.

In this episode of The New Future of Work series of the podcast, Chief Scientist Jaime Teevan and Senior Research Economist Sonia Jaffe delve into the “Personal Productivity and Well-Being” chapter of the report, beginning with why measuring productivity isn’t as easy as just observing output or counting hours worked. They also explore how people already working from home helped them better understand how people adjusted to remote work, the diversity in experiences among workers, and how we can be better coworkers to our remote colleagues whether we’re working from home or not.

https://www.microsoft.com/research

For Microsoft researchers, COVID-19 was a call to action. The reimagining of work practices had long been an area of study, but existing and new questions that needed immediate answers surfaced as companies and their employees quickly adjusted to significantly different working conditions. Teams from across the Microsoft organizational chart pooled their unique expertise together under The New Future of Work initiative. The results have informed product features designed to better support remote work and are now being used to help companies, including Microsoft, usher their workforces into a future of hybrid work.

In this episode of The New Future of Work series of the podcast, Chief Scientist Jaime Teevan and Abigail Sellen, Deputy Lab Director at Microsoft Research Cambridge in the United Kingdom, explore the dynamics of meetings and collaborations in the context of remote work. They specifically address the difference between weak and strong ties in our professional networks and why both matter to employee and company success. They also break down the phenomenon of video fatigue and share ways in which remote meetings may actually have the advantage.

https://www.microsoft.com/research

For Microsoft researchers, COVID-19 was a call to action. The reimagining of work practices had long been an area of study, but existing and new questions that needed immediate answers surfaced as companies and their employees quickly adjusted to significantly different working conditions. Teams from across the Microsoft organizational chart pooled their unique expertise together under The New Future of Work initiative. The results have informed product features designed to better support remote work and are now being used to help companies, including Microsoft, usher their workforces into a future of hybrid work.

In this episode of The New Future of Work series of the podcast, Chief Scientist Jaime Teevan and Director of Applied Science Brent Hecht of the Experiences and Devices group in Microsoft share how an internal SharePoint document led to what they believe is the largest collection of research on the pandemic’s impact on work. They’ll discuss the role of research during times of disruption, the widening scope of productivity tools, why going back to work two to three days a week is ideal, and what else companies should keep in mind as they decide on new work models.

https://www.microsoft.com/research

In the world of economics, researchers at Microsoft are examining a range of complex systems—from those that impact the technologies we use to those that inform the laws and policies we create—through the lens of a social science that goes beyond the numbers to better understand people and society.

In this episode, Senior Principal Researcher Hunt Allcott talks with Postdoctoral Researcher Evan Rose about Allcott’s work exploring the everyday decisions people face, like buying fuel-efficient cars or taking out payday loans, and how a clearer understanding of these decisions can shape meaningful public policy. Allcott shares how his and others’ research shows that policy can often have complex outcomes resulting in hidden benefits and drawbacks, as in the case of taxes on sugary beverages. The researchers also discuss why individuals often feel the competing motivations of making bad versus good decisions—a tension that often lies front-and-center in scenarios primed for behavioral public economics research.

https://www.microsoft.com/research

In the world of economics, researchers at Microsoft are examining a range of complex systems—from those that impact the technologies we use to those that inform the laws and policies we create—through the lens of a social science that goes beyond the numbers to better understand people and society.

Interviewed by Senior Principal Researcher Hunt Allcott, Economist David Rothschild discusses how the news media has evolved alongside social media and the internet, from story development to distribution of news via aggregators and wire services. Rothschild illuminates how and where people are consuming news and shares some of the strategies he’s seeing news outlets use to appeal to their audiences. He also covers research insights into media bias, misinformation, and how this knowledge could inform the future of news for the better. In addition, the researchers talk about Rothschild’s work with Project Ratio, which looks at how the news ecosystem impacts public opinion and political polarization while providing a multi-faceted approach to understanding these outcomes through data and infrastructure.

https://www.microsoft.com/research

In the world of economics, researchers at Microsoft are examining a range of complex systems—from those that impact the technologies we use to those that inform the laws and policies we create—through the lens of a social science that goes beyond the numbers to better understand people and society.

In this episode, Senior Principal Researcher Dr. Hunt Allcott speaks with Microsoft Research New England office mate and Senior Principal Researcher Dr. Greg Lewis. Together, they cover the connection between causal machine learning and economics research, the motivations of buyers and sellers on e-commerce platforms, and how ad targeting and data practices could evolve to foster a more symbiotic relationship between customers and businesses. They also discuss EconML, a Python package for estimating heterogeneous treatment effects that Lewis has worked on as part of the ALICE (Automated Learning and Intelligence for Causation and Economics) project at Microsoft Research.

https://www.microsoft.com/research

In the world of economics, researchers at Microsoft are examining a range of complex systems—from those that impact the technologies we use to those that inform the laws and policies we create—through the lens of a social science that goes beyond the numbers to better understand people and society.

In this episode, Dr. Hunt Allcott, Senior Principal Researcher at Microsoft Research New England, talks with Dr. Evan Rose, Postdoctoral Researcher, whom Allcott describes as “one of the most engaging and talented researchers in applied microeconomics today.” They’ll discuss how Rose’s experience teaching adult learners at San Quentin State Prison has resonated throughout his research, and they’ll delve into what his and others’ work is uncovering about the criminal justice system today, including the effects of incarceration and parole, impacts of ban-the-box hiring practices, and racial disparities and discrimination.

Today, people around the globe—from teachers to small-business owners to finance executives—use Microsoft Excel to make sense of the information that occupies their respective worlds, and whether they realize it or not, in doing so, they’re taking on the role of programmer.

In this episode, Senior Principal Research Manager Andy Gordon, who leads the Calc Intelligence team at Microsoft Research, and Senior Principal Researcher Simon Peyton Jones provide an inside account of the journey Excel has taken as a programming language, including the expansion of data types that has unlocked greater functionality and the release of the LAMBDA function, which makes the Excel formula language Turing-complete. They’ll talk specifically about how research has influenced Excel and vice versa, programming as a human-computer interaction challenge, and a future in which Excel is the first language for budding programmers and a tool for incorporating probabilistic reasoning into our decision-making.

https://www.microsoft.com/research

Dynamic random-access memory – or DRAM – is the most popular form of volatile computer memory in the world but it’s particularly susceptible to Rowhammer, an adversarial attack that can cause data loss and security exploits in everything from smart phones to the cloud.

Today, Dr. Stefan Saroiu, a Senior Principal Researcher in MSR’s Mobility and Networking group, explains why DRAM remains vulnerable to Rowhammer attacks today, even after several years of mitigation efforts, and then tells us how a new approach involving bespoke extensibility mechanisms for DRAM might finally hammer Rowhammer in the fight to keep data safe and secure.

Many computer science researchers set their sights on building general AI technologies that could impact hundreds of millions – or even billions – of people. But Dr. Danielle Bragg, a senior researcher at MSR’s New England lab, has a slightly smaller and more specific population in mind: the some seventy million people worldwide who use sign languages as their primary means of communication.

Today, Dr. Bragg gives us an insightful overview of the field and talks about the unique challenges and opportunities of building systems that expand access to information in line with the needs and desires of the deaf and signing community.

https://www.microsoft.com/research

MSR’s New York City lab is home to some of the best reinforcement learning research on the planet but if you ask any of the researchers, they’ll tell you they’re very interested in getting it out of the lab and into the real world. One of those researchers is Dr. Akshay Krishnamurthy and today, he explains how his work on feedback-driven data collection and provably efficient reinforcement learning algorithms is helping to move the RL needle in the real-world direction.

https://www.microsoft.com/research

Dr. Siddhartha Sen is a Principal Researcher in MSR’s New York City lab, and his research interests are, if not impossible, at least impossible sounding: optimal decision making, universal data structures, and verifiably safe AI.

Today, he tells us how he’s using reinforcement learning and HAIbrid algorithms to tap the best of both human and machine intelligence and develop AI that’s minimally disruptive, synergistic with human solutions, and safe.

This episode originally aired in August, 2018.

Kevin Scott has embraced many roles over the course of his illustrious career in technology: software developer, engineering executive, researcher, angel investor, philanthropist, and now, Chief Technology Officer of Microsoft. But perhaps no role suits him so well – or has so fundamentally shaped all the others – as his self-described role of “all-around geek.”

Today, in a wide-ranging interview, Kevin shares his insights on both the history and the future of computing, talks about how his impulse to celebrate the extraordinary people “behind the tech” led to an eponymous non-profit organization and a podcast, and… reveals the superpower he got when he was in grad school.

Dr. Devon Hjelm is a senior researcher at the Microsoft Research lab in Montreal, and today, he joins me to dive deep into his research on Deep InfoMax, a novel self-supervised learning approach to training AI models – and getting good representations – without human annotation. He also tells us how an interest in neural networks, first human and then machine, led to an inspiring career in deep learning research.

https://www.microsoft.com/research

This episode originally aired in June, 2019

You may not know who Dr. Andrew Fitzgibbon is, but if you’ve watched a TV show or movie in the last two decades, you’ve probably seen some of his work. An expert in 3D computer vision and graphics, and head of the new All Data AI group at Microsoft Research Cambridge, Dr. Fitzgibbon was instrumental in the development of Boujou, an Emmy Award-winning 3D camera tracker that lets filmmakers place virtual props, like the floating candles in Hogwarts School for Witchcraft and Wizardry, into live-action footage. But that was just his warm-up act.

On today’s podcast, Dr. Fitzgibbon tells us what he’s been working on since the Emmys in 2002, including body- and hand-tracking for powerhouse Microsoft technologies like Kinect for Xbox 360 and HoloLens, explains how research on dolphins helped build mathematical models for the human hand, and reminds us, once again, that the “secret sauce” to most innovation is often just good, old-fashioned hard work.

https://www.microsoft.com/research

This episode originally aired in April, 2018

Emotions are fundamental to human interaction, but in a world where humans are increasingly interacting with AI systems, Dr. Mary Czerwinski, Principal Researcher and Research Manager of the Visualization and Interaction for Business and Entertainment group at Microsoft Research, believes emotions may be fundamental to our interactions with machines as well. And through her team’s work in affective computing, the quest to bring Artificial Emotional Intelligence – or AEI – to our computers may be closer than we think.

Today, Dr. Czerwinski tells us how a cognitive psychologist found her way into the research division of the world’s largest software company, suggests that rather than trying to be productive 24/7, we should aim for Emotional Homeostasis instead, and tells us how, if we do it right, our machines could become a sort of “emotional at-work DJ,” sensing and responding to our emotional states, and helping us to become happier and more productive at the same time.

This episode originally aired in April, 2019.

We hear a lot these days about “AI for good” and the efforts of many companies to harness the power of artificial intelligence to solve some of our biggest environmental challenges. It’s rare, however, that you find a company willing to bring its environmental bona fides all the way to the C Suite. Well, meet Dr. Lucas Joppa. A former environmental and computer science researcher at MSR who was tapped in 2017 to become the company’s first Chief Environmental Scientist, Dr. Joppa is now the Chief Environmental Officer at Microsoft, another first, and is responsible for managing the company’s overall environmental sustainability efforts from operations to policy to technology.

Today, Dr. Joppa shares how his love for nature and the joy of discovery actually helped shape his career path, and tells us all about AI for Earth, a multi-year, multi-million dollar initiative to deploy the full scale of Microsoft’s products, policies and partnerships across four key areas of agriculture, water, biodiversity and climate, and transform the way society monitors, models, and ultimately manages Earth’s natural resources.

This episode originally aired in December, 2017

On today’s episode, neuroscientist and virtual reality researcher, Dr. Mar Gonzalez Franco, talks about her work in VR, explains how avatars can help increase our empathy and reduce our biases via role play, and addresses the misconceptions that exist between the immersive experiences of virtual reality and psychedelic drugs.

Forty years ago, database research was an “exotic” field and, because of its business data processing reputation, was not considered intellectually interesting in academic circles. But that didn’t deter Dr. Philip Bernstein, now a Distinguished Scientist in MSR’s Data Management, Exploration and Mining group, and a pioneer in the field.

Today, Dr. Bernstein talks about his pioneering work in databases over the years and tells us all about Project Orleans, a distributed systems programming framework that makes life easier for programmers who aren’t distributed systems experts. He also talks about the future of database systems in a cloud scale world, and reveals where he finds his research sweet spot along the academic industrial spectrum.

https://www.microsoft.com/research

Brad Smith is the President of Microsoft and leads a team of more than 1400 employees in 56 countries. He plays a key role in spearheading the company’s work on critical issues involving the intersection of technology and society. In his spare time, he’s also an author!

We were fortunate to catch up with Brad who, late on a Friday afternoon, sat down with me in the booth to talk about his new book, Tools and Weapons: The Promise and the Peril of the Digital Age, and revealed the top ten tech policy issues he believes will shape our own century’s roaring 20s. He also gave us a peek inside the life of a person the New York Times has described a “de facto ambassador for the technology industry at large” – himself!

https://www.microsoft.com/research

Rangan Majumder is the Partner Group Program Manager of Microsoft’s Search and AI, and he has a simple goal: to make the world smarter and more productive. But nobody said simple was easy, so he and his team are working on better – and faster – ways to help you find the information you’re looking for, anywhere you’re looking for it.

Today, Rangan talks about how three big trends have changed the way Microsoft is building – and sharing – AI stacks across product groups. He also tells us about Project Turing, an internal deep learning moonshot that aims to harness the resources of the web and bring the power of deep learning to a search box near you.

https://www.microsoft.com/research

Dr. Behnaz Arzani is a senior researcher in the Mobility and Networking group at MSR, and she feels your pain. At least, that is, if you’re a network operator trying to troubleshoot an incident in a datacenter. Her research is all about getting networks to manage themselves, so your life is as pain-free as possible.

On today’s podcast, Dr. Arzani tells us why it’s so hard to identify and resolve networking problems and then explains how content-aware, or domain-customized, auto ML frameworks might help. She also tells us what she means when she says she wants to get humans out of the loop, and reveals how a competitive streak and a comment from her high school principal set her on the path to a career in high tech research.

https://www.microsoft.com/research

If you want an inside look at how a research idea goes from project to prototype to product, you should hang out with Gavin Jancke for a while. He’s the General Manager of Engineering for MSR Redmond where he created – and runs – the Central Engineering Group. Over the past two decades, he’s overseen more than seven hundred software and hardware engineering projects, from internal MSR innovations to Microsoft product group partnerships.

Today, Gavin takes us on a guided tour of the research engineering landscape and the engineering pipeline, recounting some of Central Engineering’s greatest hits. He also explains how the lab determines which projects get engineering resources, and reveals how one of his own projects ended up in the Museum of Modern Art.

https://www.microsoft.com/research

Dr. Debadeepta Dey is a Principal Researcher in the Adaptive Systems and Interaction group at MSR and he’s currently exploring several lines of research that may help bridge the gap between perception and planning for autonomous agents, teaching them make decisions under uncertainty and even to stop and ask for directions when they get lost!

On today’s podcast, Dr. Dey talks about how his latest work in meta-reasoning helps improve modular system pipelines and how imitation learning hits the ML sweet spot between supervised and reinforcement learning. He also explains how neural architecture search helps enlighten the “dark arts” of neural network training and reveals how boredom, an old robot and a several “book runs” between India and the US led to a rewarding career in research.

https://www.microsoft.com/research

Dr. Donald Kossmann is a Distinguished Scientist who thinks big, and as the Director of Microsoft Research’s flagship lab in Redmond, it’s his job to inspire others to think big, too. But don’t be fooled. For him, thinking big involves what he calls thinking backwards, a framework of imagining the future, defining progress in reverse order and executing against landmarks along an uncertain path.

On today’s podcast, Dr. Kossmann reflects on his life as a database researcher and tells us how Socrates, an innovative database-as-a-service architecture, is re-envisioning traditional database design. He also reveals the five superpowers of Microsoft Research and how we can improve science… with marketing.

https://www.microsoft.com/research

In a world where productivity is paramount and only a handful of people have personal assistants, many of us are frustrated by the amount of time we spend in meetings, and worse, the amount time we spend planning, scheduling and rescheduling those meetings! Fortunately, Dr. Pamela Bhattacharya, a Principal Applied Scientist in Microsoft’s Outlook group, wants to turn your email into your own personal assistant. And a smart one at that!

Today, Dr. Bhattacharya tells us all about Scheduler, Microsoft’s virtual personal assistant, and how her team is using machine learning to put the “I” in intelligent PDAs. She also talks about how understanding different levels of automation can help us set the right expectations for our experience with AI, and explains how, in the workplace of the future, we might actually achieve more by doing less.

https://www.microsoft.com/research

There’s an old adage that says if you fail to plan, you plan to fail. But when it comes to AI, Dr. Saleema Amershi, a principal researcher in the Adaptive Systems and Interaction group at Microsoft Research, contends that if you plan to fail, you’re actually more likely to succeed! She’s an advocate of calling failure what it is, getting ahead of it in the AI development cycle and making end-users a part of the process.

Today, Dr. Amershi talks about life at the intersection of AI and HCI and does a little AI myth-busting. She also gives us an overview of what – and who – it takes to build responsible AI systems and reveals how a personal desire to make her own life easier may make your life easier too.

https://www.microsoft.com/research

Dr. Jianfeng Gao is a veteran computer scientist, an IEEE Fellow and the current head of the Deep Learning Group at Microsoft Research. He and his team are exploring novel approaches to advancing the state-of-the-art on deep learning in areas like NLP, computer vision, multi-modal intelligence and conversational AI.

Today, Dr. Gao gives us an overview of the deep learning landscape and talks about his latest work on Multi-task Deep Neural Networks, Unified Language Modeling and vision-language pre-training. He also unpacks the science behind task-oriented dialog systems as well as social chatbots like Microsoft Xiaoice, and gives us some great book recommendations along the way!

https://www.microsoft.com/research

Dr. Sriram Rajamani is a Distinguished Scientist and the Managing Director of the Microsoft Research lab in Bangalore. He’s dedicated his career to advancing globally applicable science in the testbed that is India. He is, by any measure, a world-class researcher and leader. He’s also, as you’ll find out shortly, a world-class storyteller!

Today, Dr. Rajamani talks about the unique challenges and opportunities of leading MSR’s research efforts in India and what it takes to build a robust research ecosystem in a country of huge disparities. He also dispels some preconceptions about poor and marginalized populations and explains why ‘frugal innovation’ may be one key to solving societal scale problems.

https://www.microsoft.com/research

This episode originally aired in May, 2019.

Machine learning is a powerful tool that enables computers to learn by observing the world, recognizing patterns and self-training via experience. Much like humans. But while machines perform well when they can extract knowledge from large amounts of labeled data, their learning outcomes remain vastly inferior to humans when data is limited. That’s why Dr. Patrice Simard, Distinguished Engineer and head of the Machine Teaching group at Microsoft, is using actual teachers to help machines learn, and enable them to extract knowledge from humans rather than just data.

Today, Dr. Simard tells us why he believes any task you can teach to a human, you should be able to teach to a machine; explains how machines can exploit the human ability to decompose and explain concepts to train ML models more efficiently and less expensively; and gives us an innovative vision of how, when a human teacher and a machine learning model work together in a real-time interactive process, domain experts can leverage the power of machine learning without machine learning expertise.

This episode originally aired in May, 2019.

If you’re in software development, Dr. Tom Zimmermann, a senior researcher at Microsoft Research in Redmond, wants you to be more productive, and he’s here to help. How, you might ask? Well, while productivity can be hard to measure, his research in the Empirical Software Engineering group is attempting to do just that by using insights from actual data, rather than just gut feelings, to improve the software development process.

On today’s podcast, Dr. Zimmermann talks about why we need to rethink productivity in software engineering, explains why work environments matter, tells us how AI and machine learning are impacting traditional software workflows, and reveals the difference between a typical day and a good day in the life of a software developer, and what it would take to make a good day typical!

This episode originally aired in May, 2019.
Dr. John Langford, a partner researcher in the Machine Learning group at Microsoft Research New York City, is a reinforcement learning expert who is working, in his own words, to solve machine learning. Rafah Hosn, also of MSR New York, is a principal program manager who’s working to take that work to the world. If that sounds like big thinking in the Big Apple, well, New York City has always been a “go big, or go home” kind of town, and MSR NYC is a “go big, or go home” kind of lab.

Today, Dr. Langford explains why online reinforcement learning is critical to solving machine learning and how moving from the current foundation of a Markov decision process toward a contextual bandit future might be part of the solution. Rafah Hosn talks about why it’s important, from a business perspective, to move RL agents out of simulated environments and into the open world, and gives us an under-the-hood look at the product side of MSR’s “research, incubate, transfer” process, focusing on real world reinforcement learning which, at Microsoft, is now called Azure Cognitive Services Personalizer.

Dr. Sébastien Bubeck is a mathematician and a senior researcher in the Machine Learning and Optimization group at Microsoft Research. He’s also a self-proclaimed “bandit” who claims that, despite all the buzz around AI, it’s still a science in its infancy. That’s why he’s devoted his career to advancing the mathematical foundations behind the machine learning algorithms behind AI.

Today, Dr. Bubeck explains the difficulty of the multi-armed bandit problem in the context of a parameter- and data-rich online world. He also discusses a host of topics from randomness and convex optimization to metrical task systems and log n competitiveness to the surprising connection between Gaussian kernels and what he calls some of the most beautiful objects in mathematics.

This episode first aired in November, 2018.

Dr. Christopher Bishop is quite a fellow. Literally. Fellow of the Royal Academy of Engineering. Fellow of Darwin College in Cambridge, England. Fellow of the Royal Society of Edinburgh. Fellow of The Royal Society. Microsoft Technical Fellow. And one of the nicest fellows you’re likely to meet! He’s also Director of the Microsoft Research lab in Cambridge, where he oversees a world-class portfolio of research and development endeavors in machine learning and AI.

Today, Dr. Bishop talks about the past, present and future of AI research, explains the No Free Lunch Theorem, talks about the modern view of machine learning (or how he learned to stop worrying and love uncertainty), and tells how the real excitement in the next few years will be the growth in our ability to create new technologies not by programming machines but by teaching them to learn.

https://www.microsoft.com/research

With all the buzz surrounding AI, it can be tempting to envision it as a stand-alone entity that optimizes for accuracy and displaces human capabilities. But Dr. Besmira Nushi, a senior researcher in the Adaptive Systems and Interaction group at Microsoft Research, envisions AI as a cooperative entity that enhances human capabilities and optimizes for team performance.

On today’s podcast, Dr. Nushi talks about what it takes to develop collaborative AI systems and unpacks the unique challenges machine learning engineers face in their version of the software development cycle. She also reveals why understanding the “terrain of failure” can help researchers develop AI systems that perform as well in the real world as they do in the lab.

https://www.microsoft.com/research

Deep learning methodologies like supervised learning have been very successful in training machines to make predictions about the world. But because they’re so dependent upon large amounts of human-annotated data, they’ve been difficult to scale. Dr. Phil Bachman, a researcher at MSR Montreal, would like to change that, and he’s working to train machines to collect, sort and label their own data, so people don’t have to.

Today, Dr. Bachman gives us an overview of the machine learning landscape and tells us why it’s been so difficult to sort through noise and get to useful information. He also talks about his ongoing work on Deep InfoMax, a novel approach to self-supervised learning, and reveals what a conversation about ML classification problems has to do with Harrison Ford’s face.

https://www.microsoft.com/research

There’s a lot of excitement around self-driving cars, delivery drones, and other intelligent, autonomous systems, but before they can be deployed at scale, they need to be both reliable and safe. That’s why Gurdeep Pall, CVP of Business AI at Microsoft, and Dr. Ashish Kapoor, who leads research in Aerial Informatics and Robotics, are using a simulated environment called AirSim to reduce the time, cost and risk of the testing necessary to get autonomous agents ready for the open world.

Today, Gurdeep and Ashish discuss life at the intersection of machine learning, simulation and autonomous systems, and talk about the challenges we face as we transition from a world of automation to a world of autonomy. They also tell us about Game of Drones, an exciting new drone racing competition where the goal is to imbue flying robots with human-level perception and decision making skills… on the fly.

https://www.microsoft.com/research

Dr. Sumit Gulwani is a programmer’s programmer. Literally. A Partner Research Manager in the Program Synthesis, or PROSE, group at Microsoft Research, Dr. Gulwani is a leading researcher in program synthesis and the inventor of many intent-understanding, programming-by-example and programming-by-natural language technologies – aka, the automation of “what I meant to do and wanted to do, but my computer wouldn’t let me” tasks.

Today, Dr. Gulwani gives us an overview of the exciting “now” and promising future of program synthesis; reveals some fascinating new applications and technical advances; tells us the story behind the creation of Excel’s popular Flash Fill feature (and how a Flash Fill Fail elicited a viral tweet that paved the way for new domain investments); and shares a heartwarming story of how human empathy facilitated an “ah-ha math moment” in the life of a child, and what that might mean to computer scientists, educators and even tech companies in the future.

https://www.microsoft.com/research

Computer programming has often been perceived as the exclusive domain of computer scientists and software engineers. But that’s changing, thanks to the work of people like Dr. Thomas Ball, a Partner Researcher in the RiSE group at Microsoft Research, and Dr. Teddy Seyed, a post-doctoral researcher in the same group. Their goal is to make programming accessible to non-programmers in places like the classroom, the workshop… and even the runway!

On today’s podcast, Tom and Teddy talk about physical computing through platforms like MakeCode, a simplified programming environment that makes it easier for young people – and other computer science neophytes – to start coding with programmable microcontrollers. They also tell us all about Project Brookdale, where they did a collaborative fashion show that gave emerging designers the tools to embed technology in their garments and produce wearables you’d actually want to be seen in!

https://www.microsoft.com/research

Remember when a hard drive that could hold a terabyte of data was a big deal? Well, we’re now in an era where peta-, exa- and even zetta-bytes are the bytes of the day, and it turns out it’s hard to fit that many zeroes on a hard drive. That’s where Dr. Ant Rowstron, Deputy Lab Director of Microsoft Research Cambridge, and Mark Russinovich, Chief Technical Officer of Azure, come in. Their respective teams are working on paradigm-breaking solutions to give us phenomenal storage power in an itty-bitty living space.

Today, Ant and Mark discuss their roles in the development of new optical technologies, like Project Silica, for cloud-scale storage demands, and talk about the Optics for the Cloud Research Alliance, an exciting new collaboration between academic researchers and MSR. They also explain how just the right mix of innovation and engineering can make the cloud more powerful and less expensive to use and, at the same time, deliver “forever” storage that’s both dishwasher and microwave safe!

https://www.microsoft.com/research

Jenny Sabin is an architectural designer, a professor, a studio principal and MSR’s current Artist in Residence. Asta Roseway is a principal research designer, a “fusionist” and the co-founder of the Artist in Residence program at Microsoft Research. The two, along with a stellar multi-disciplinary team, recently completed the installation of Ada, the first interactive architectural pavilion powered by AI, in the heart of the Microsoft Research building in Redmond.

On today’s podcast, Jenny and Asta talk about life at the intersection of art and science; tell us why the Artist in Residence program pushes the boundaries of technology in unexpected ways; and reveal their vision of the future of bio-inspired, human-centered, AI-infused architecture.

https://www.microsoft.com/research

Machine learning is a powerful tool that enables conversational agents to provide general question-answer services. But in domains with more specific taxonomies – or simply for requests that are longer and more complicated than “Play Baby Shark” – custom conversational AI has long been the province of large enterprises with big budgets. But not for long, thanks to the work of Dr. Riham Mansour, a Principal Software Engineering Manager for Microsoft’s Language Understanding Service, or LUIS. She and her colleagues are using the emerging science of machine teaching to help domain experts build bespoke AI models with little data and no machine learning expertise.

On today’s podcast, Dr. Mansour gives us a brief history of conversational machines at Microsoft; tells us all about LUIS, one of the first Microsoft products to deploy machine teaching concepts in real world verticals; and explains how an unlikely combination of engineering skills, science skills, entrepreneurial skills – and not taking no for an answer – helped make automated customer engagement and business functions more powerful, more accessible and more intelligent!

https://www.microsoft.com/research

Dr. Craig Costello is in the business of safeguarding your secrets. And he uses math to do it. A researcher in the Security and Cryptography group at Microsoft Research, Dr. Costello is among a formidable group of code makers (aka cryptographers) who make it their life’s work to protect the internet against adversarial code breakers (aka cryptanalysts), both those that exist today in our classical computing world, and those that will exist in a quantum computing future.

On today’s podcast, Dr. Costello gives us a battlefield update in the ongoing crypto wars; talks about different approaches to post quantum cryptography and explains why he believes isogeny-based primitives are among the most promising; and reassures us that, as long as the battle goes on, cryptographers will continue to work very hard on the very hard math they hope will protect us from hackers and attackers, even in the age of quantum computers.

https://www.microsoft.com/research

Using technology to help us improve our health is nothing new: a quick web search returns hundreds of apps and devices claiming to help us get fit, quit smoking, master anxiety or just “find our center.” What is new is a serious cohort of researchers exploring how artificial emotional intelligence, or AEI, could help us understand ourselves better and, when used in concert with human caregivers, enhance our well-being. One of those researchers is Jina Suh, a former Xbox developer who got hooked on research and is now an RSDE in the Human Understanding and Empathy group at MSR, as well as a PhD student in computer science at the University of Washington.

On today’s podcast, Jina shares her passion for creating technologies that promote emotional resilience and mental health; gives us an inside look at an innovative research collaboration that aims to improve collaborative care for cancer patients with depression; and tells us an emotional story of how, on the brink of quitting her job, she found inspiration to get back in the game and begin a new career in research for human well-being.

https://www.microsoft.com/research

If someone asked you what snow leopards and Vincent Van Gogh have in common, you might think it was the beginning of a joke. It’s not, but if it were, Mark Hamilton, a software engineer in Microsoft’s Cognitive Services group, budding PhD student and frequent Microsoft Research collaborator, would tell you the punchline is machine learning. More specifically, Microsoft Machine Learning for Apache Spark (MMLSpark for short), a powerful yet elastic open source machine learning library that’s finding its way beyond business and into “AI for Good” applications such as the environment and the arts.

Today, Mark talks about his love of mathematics and his desire to solve big, crazy, core knowledge sized problems; tells us all about MMLSpark and how it’s being used by organizations like the Snow Leopard Trust and the Metropolitan Museum of Art; and reveals how the persuasive advice of a really smart big sister helped launch an exciting career in AI research and development.

https://www.microsoft.com/research

Dr. Eyal Ofek is a senior researcher at Microsoft Research and his work deals mainly with, well, reality. Augmented and virtual reality, to be precise. A serial entrepreneur before he came to MSR, Dr. Ofek knows a lot about the “long nose of innovation” and what it takes to bring a revolutionary new technology to a world that’s ready for it.

On today’s podcast, Dr. Ofek talks about the unique challenges and opportunities of augmented and virtual reality from both a technical and social perspective; tells us why he believes AR and VR have the potential to be truly revolutionary, particularly for people with disabilities; explains why, while we’re doing pretty well in the virtual worlds of sight and sound, our sense of virtual touch remains a bit more elusive; and reveals how, if he and his colleagues are wildly successful, it won’t be that long before we’re living in a whole new world of extension, expansion, enhancement and equality.

https://www.microsoft.com/research

Dr. Susan Dumais knows you have things to do, and if you need help finding stuff to get them done (and you probably do) then her long and illustrious career in search technologies has been worth it. Situated firmly in Louis Pasteur’s quadrant of the research grid (the square where you answer “yes” to both the quest for fundamental understanding and use-based applications) the Microsoft Technical Fellow, and Deputy Lab Director of MSR AI, has made finding information the focus of her career, and has probably made your life a little more productive in the process.

Today, Dr. Dumais tells us how the landscape of information retrieval has evolved over the past twenty years; reminds us that queries don’t fall from the sky but are grounded in the context of real people, real events and real time; talks about her current interest in non-web-based search (or how I can easily put my hands on my own digital belongings) and reveals what apples and Michael Jordan have in common with search research.

https://www.microsoft.com/research

In 2018, Microsoft launched the Microsoft AI Residency Program, a year-long, expanded research experience designed to give recent graduates in a variety of fields the opportunity to work alongside prominent researchers at MSR on cutting edge AI technologies to solve real-world problems. Dr. Brian Broll was one of them. A newly minted PhD in Computer Science from Vanderbilt University, Dr. Broll was among the inaugural cohort of AI residents who spent a year working on machine learning in game environments and is on the pod to talk about it!

Today, Dr. Broll gives us an overview of the work he did and the experience he had as a Microsoft AI Resident, talks about his passion for making complex concepts easier and more accessible to novices and young learners, and tells us how growing up on a dairy farm in rural Minnesota helped prepare him for a life in computer science solving some of the toughest problems in AI.

https://www.microsoft.com/research

Dr. Ed Cutrell is a Principal Researcher in the Ability group at Microsoft Research and he’s convinced that great technology should be available to everyone. Working in the fields of Accessibility and Information and Communication Technologies for Development (aka ICT4D), his research has explored computing solutions for people across the resource and ability spectrum, both here and around the world.

Today, Dr. Cutrell gives us an overview of his work in the disability and inclusive design space, explains the vital importance of interdisciplinarity – a fancy way of saying many ways of thinking and many ways of knowing – and tells us how a dumb phone beat a smart tablet in rural India… and what that meant to researchers.

https://www.microsoft.com/research

As computing moves to the cloud, there is an increasing need for privacy in AI. In an ideal world, users would have the ability to compute on encrypted data without sacrificing performance. Enter Dr. Olli Saarikivi, a post-doctoral researcher in the RiSE group at MSR. He, along with a stellar group of cross-disciplinary colleagues, are bridging the gap with CHET, a compiler and runtime for homomorphic evaluation of tensor programs, that keeps data private while making the complexities of homomorphic encryption schemes opaque to users.

On today’s podcast, Dr. Saarikivi tells us all about CHET, gives us an overview of some of his other projects, including Parasail, a novel approach to parallelizing seemingly sequential applications, and tells us how a series of unconventional educational experiences shaped his view of himself, and his career as a researcher.

https://www.microsoft.com/research

The ability to read and understand unstructured text, and then answer questions about it, is a common skill among literate humans. But for machines? Not so much. At least not yet! And not if Dr. T.J. Hazen, Senior Principal Research Manager in the Engineering and Applied Research group at MSR Montreal, has a say. He’s spent much of his career working on machine speech and language understanding, and particularly, of late, machine reading comprehension, or MRC.

On today’s podcast, Dr. Hazen talks about why reading comprehension is so hard for machines, gives us an inside look at the technical approaches applied researchers and their engineering colleagues are using to tackle the problem, and shares the story of how an a-ha moment with a Rubik’s Cube inspired a career in computer science and a quest to teach computers to answer complex, text-based questions in the real world.

https://microsoft.com/research

In an era of unprecedented advances in AI and machine learning, current gen systems and networks are being challenged by an unprecedented level of complexity and cost. Fortunately, Dr. Ganesh Ananthanarayanan, a researcher in the Mobility and Networking group at MSR, is up for a challenge. And, it seems, the more computationally intractable the better! A prolific researcher who’s interested in all aspects of systems and networking, he’s on a particular quest to extract value from live video feeds and develop “killer apps” that will have a practical impact on the world.

Today, Dr. Ananthanarayanan tells us all about Video Analytics for Vision Zero (an award-winning “killer app” that aims to reduce traffic-related fatalities to zero), gives us a wide-angle view of his work in geo-distributed data analytics and client-cloud networking, and explains how the duration and difficulty of a Test Cricket match provides an invaluable lesson for success in life and research.

https://www.microsoft.com/research

Dr. Nathalie Riche envisions a future in which all of our data will be accessible, meaningful, compelling and artistic. And as a researcher in human computer interaction and information visualization at Microsoft Research, she’s working on technical tools that will help us wrangle our data, extract knowledge from it, and communicate with it in a memorable, persuasive and aesthetically pleasing way. In other words, she wants our data to be both smart… and beautiful!

Today, Dr. Riche shares her passion for the art of data driven storytelling, reveals the two superpowers of data visualization, gives us an inside look at some innovative projects designed to help us th(ink) with digital ink, and tells the story of how a young woman with an artist’s heart headed into computer science, took a detour to the beach, paid for it with research and ended up with a rewarding career that brings both art and computing together.

https://www.microsoft.com/research

This episode first aired in January, 2018. When we look at a skyscraper or a suspension bridge, a simple search engine box on a screen looks tiny by comparison. But Dr. Simon Peyton Jones would like to remind us that computer programs, with hundreds of millions of lines of code, are actually among the largest structures human beings have ever built. A principle researcher at the Microsoft Research Lab in Cambridge, England, co-developer of the programming language Haskell, and a Fellow of Britain’s Royal Society, Simon Peyton Jones has dedicated his life to this very particular kind of construction work.

Today, Dr. Peyton Jones shares his passion for functional programming research, reveals how a desire to help other researchers write and present better turned him into an unlikely YouTube star, and explains why, at least in the world of programming languages, purity is embarrassing, laziness is cool, and success should be avoided at all costs.

https://www.microsoft.com/research

This episode first aired in March, 2018. There’s a big gap between memory and storage, and Dr. Anirudh Badam, of the Systems Research Group at Microsoft Research, wants to close it. With projects like Navamem, which explores how systems can get faster and better by adopting new memory technologies, and HashCache, which brings with it the promise of storage for the next billion, he just might do it.

Today, Dr. Badam discusses the historic trade-offs between volatile and non-volatile memory, shares how software-defined batteries are changing the power-supply landscape, talks about how his research is aiming for the trifecta of speed, cost and capacity in new memory technologies, and reminds us, once again, how one good high school physics teacher can inspire the next generation of scientific discovery.

https://www.microsoft.com/research

Dr. Johannes Gehrke is a Microsoft Technical Fellow and head of Architecture and Machine Learning for the Intelligent Communications and Conversations Cloud in Microsoft’s Experiences and Devices division. But lest you think his lofty position makes him in any way superior to you, let me tell you, he knows who works for whom, and he’ll be the first to tell you that you are his boss!

On today’s podcast, Dr. Gehrke frames the new, cloud-powered work world as a fast paced, widely-distributed workplace that demands real-time decision-making and collaboration – and explains how products like Microsoft Teams are meeting those demands – and tells us, both directly and indirectly, about the future of work, which for Microsoft, involves a pivot from an app-centric approach to a people-centric approach where, by using an AI-infused productivity suite coupled with the power of the cloud, we can essentially “hire Microsoft” to help us get our work done.

This episode first aired in November, 2017 - Dr. Jaime Teevan has a lot to say about productivity in a fragmented culture, and some solutions that seem promising, if somewhat counterintuitive.

Dr. Teevan is a Microsoft researcher, University of Washington Affiliate Professor, and the mother of 4 young boys. Today she talks about what she calls the productivity revolution, and explains how her research in micro-productivity – making use of short fragments of time to help us accomplish larger tasks – could help us be more productive, and experience a better quality of life at the same time.

https://microsoft.com/research

This episode first aired in January, 2018. As the reality of artificial intelligence continues to capture our imagination, and critical AI systems enter our world at a rapid pace, Dr. Ece Kamar, a senior researcher in the Adaptive Systems and Interaction Group at Microsoft Research, is working to help us understand AI’s far-reaching implications, both as we use it, and as we build it.

Today, Dr. Kamar talks about the complementarity between humans and machines, debunks some common misperceptions about AI, reveals how we can overcome bias and blind spots by putting humans in the AI loop, and argues convincingly that, despite everything machines can do (and they can do a lot), humans are still “the real deal.”

https://www.microsoft.com/research

If you’re like me, you’re no longer amazed by how all your technologies can work for you. Rather, you’ve begun to take for granted that they simply should work for you. Instantly. All together. All the time. The fact that you’re not amazed is a testimony to the work that people like Dr. Lidong Zhou, Assistant Managing Director of Microsoft Research Asia, do every day. He oversees some of the cutting-edge systems and networking research that goes on behind the scenes to make sure you’re not amazed when your technologies work together seamlessly but rather, can continue to take it for granted that they will!

Today, Dr. Zhou talks about systems and networking research in an era of unprecedented systems complexity and what happens when old assumptions don’t apply to new systems, explains how projects like CloudBrain are taking aim at real-time troubleshooting to address cloud-scale, network-related problems like “gray failure,” and tells us why he believes now is the most exciting time to be a systems and networking researcher.

Dr. Chris Bishop is a Microsoft Technical Fellow and director of MSR Cambridge, where he oversees an impressive portfolio of research including machine learning, AI, healthcare and gaming. Phil Spencer is the Executive Vice President of Gaming at Microsoft where he oversees everything from the design of the next Xbox console to the creation and release of blockbuster properties like Halo, Gears of War and Forza Motorsport. These two powerhouse executives are pushing the boundaries of creativity, technical innovation and fun across the spectrum of gaming genres and devices for nearly 2 billion gamers around the world.

On today’s podcast, Chris and Phil discuss their respective roles in Microsoft’s gaming ecosystem, revealing a sort of “enrichment pipeline” that flows all the way from researcher to developer to gamer. They also give us an inside look at the close collaboration between the world-class research organization of MSR and the world-class gaming franchise of Xbox, highlighting Microsoft’s unique ability to deliver the tools, talent and resources that fuel innovation and help shape the future of gaming.

http://www.microsoft.com/research

You may not know who Dr. Andrew Fitzgibbon is, but if you’ve watched a TV show or movie in the last two decades, you’ve probably seen some of his work. An expert in 3D computer vision and graphics, and head of the new All Data AI group at Microsoft Research Cambridge, Dr. Fitzgibbon was instrumental in the development of Boujou, an Emmy Award-winning 3D camera tracker that lets filmmakers place virtual props, like the floating candles in Hogwarts School for Witchcraft and Wizardry, into live-action footage. But that was just his warm-up act.

On today’s podcast, Dr. Fitzgibbon tells us what he’s been working on since the Emmys in 2002, including body- and hand-tracking for powerhouse Microsoft technologies like Kinect for Xbox 360 and HoloLens, explains how research on dolphins helped build mathematical models for the human hand, and reminds us, once again, that the “secret sauce” to most innovation is often just good, old-fashioned hard work.

If you’ve recently found it more difficult to focus your attention for a lengthy stretch of time in order to get a complex task done… or worse, found it difficult even to find a lengthy stretch of time in which to try, you’re not alone. And actually, you’re in luck. Dr. Shamsi Iqbal, a senior researcher in the Information and Data Sciences group at Microsoft Research, wants to help you manage your attention better and be more productive at the same time. And she’s using technology to do it!

On today’s podcast, Dr. Iqbal tells us about her work in the field of micro-productivity, a line of research that takes aim at the short spurts of time she calls micro-moments that we otherwise might have considered too short to get anything useful done. She also explains why distraction can be good for us and gives us some advice on how to make the most of our cognitive resources, whether by setting aside time to tackle big tasks in the traditional way or by breaking them down into micro-tasks… and “outsourcing” them to ourselves!

Machine learning is a powerful tool that enables computers to learn by observing the world, recognizing patterns and self-training via experience. Much like humans. But while machines perform well when they can extract knowledge from large amounts of labeled data, their learning outcomes remain vastly inferior to humans when data is limited. That’s why Dr. Patrice Simard, Distinguished Engineer and head of the Machine Teaching group at Microsoft, is using actual teachers to help machines learn, and enable them to extract knowledge from humans rather than just data.

Today, Dr. Simard tells us why he believes any task you can teach to a human, you should be able to teach to a machine; explains how machines can exploit the human ability to decompose and explain concepts to train ML models more efficiently and less expensively; and gives us an innovative vision of how, when a human teacher and a machine learning model work together in a real-time interactive process, domain experts can leverage the power of machine learning without machine learning expertise.

If you’re in software development, Dr. Tom Zimmermann, a senior researcher at Microsoft Research in Redmond, wants you to be more productive, and he’s here to help. How, you might ask? Well, while productivity can be hard to measure, his research in the Empirical Software Engineering group is attempting to do just that by using insights from actual data, rather than just gut feelings, to improve the software development process.

On today’s podcast, Dr. Zimmermann talks about why we need to rethink productivity in software engineering, explains why work environments matter, tells us how AI and machine learning are impacting traditional software workflows, and reveals the difference between a typical day and a good day in the life of a software developer, and what it would take to make a good day typical!

When was the last time you had a meaningful conversation with your computer… and felt like it truly understood you? Well, if Dr. Xuedong Huang, a Microsoft Technical Fellow and head of Microsoft’s Speech and Language group, is successful, you will. And if his track record holds true, it’ll be sooner than you think!

On today’s podcast, Dr. Huang talks about his role as Microsoft’s Chief Speech Scientist, gives us some inside details on the latest milestones in speech and language technology, and explains how mastering speech recognition, translation and conversation will move machines further along the path from “perceptive AI” to “cognitive AI” and that much closer to truly human intelligence.

Dr. John Langford, a partner researcher in the Machine Learning group at Microsoft Research New York City, is a reinforcement learning expert who is working, in his own words, to solve machine learning. Rafah Hosn, also of MSR New York, is a principal program manager who’s working to take that work to the world. If that sounds like big thinking in the Big Apple, well, New York City has always been a “go big, or go home” kind of town, and MSR NYC is a “go big, or go home” kind of lab.

Today, Dr. Langford explains why online reinforcement learning is critical to solving machine learning and how moving from the current foundation of a Markov decision process toward a contextual bandit future might be part of the solution. Rafah Hosn talks about why it’s important, from a business perspective, to move RL agents out of simulated environments and into the open world, and gives us an under-the-hood look at the product side of MSR’s “research, incubate, transfer” process, focusing on real world reinforcement learning which, at Microsoft, is now called Azure Cognitive Services Personalizer.

If you want to know what’s going on in the world of human computer interaction research, or what’s new at the CHI Conference on Human Factors in Computing Systems, you should hang out with Dr. Ken Hinckley, a principal researcher and research manager in the EPIC group at Microsoft Research, and Dr. Merrie Ringel Morris, a principal researcher and research manager in the Ability group. Both are prolific HCI researchers who are seeking, from different angles, to augment the capability of technologies and improve the experiences people have with them.

On today’s podcast, we get to hang out with both Dr. Hinckley and Dr. Morris as they talk about life at the intersection of hardware, software and human potential, discuss how computers can enhance human lives, especially in some of the most marginalized populations, and share their unique approaches to designing and building technologies that really work for people and for society.

In the world of relational databases, structured query language, or SQL, has long been King of the Queries, primarily because of its ubiquity and unparalleled performance. But many users prefer a mix of imperative programming, along with declarative SQL, because its user-defined functions (or UDFs) allow for good software engineering practices like modularity, readability and re-usability. Sadly, these benefits have traditionally come with a huge performance penalty, rendering them impractical in most situations. That bothered Dr. Karthik Ramachandra, a Senior Applied Scientist at Microsoft Research India, so he’s spent a great deal of his career working on improving an imperative complement to SQL in database systems.

Today, Dr. Ramachandra gives us an overview of the historic trade-offs between declarative and imperative programming paradigms, tells us some fantastic stories, including The Tale of Two Engineers and The UDF Story, Parts 1 and 2, and introduces us to Froid – that’s F-R-O-I-D, not the Austrian psychoanalyst – which is an extensible, language-agnostic framework for optimizing imperative functions in databases, offering the benefits of UDFs without sacrificing performance.

We hear a lot these days about “AI for good” and the efforts of many companies to harness the power of artificial intelligence to solve some of our biggest environmental challenges. It’s rare, however, that you find a company willing to bring its environmental bona fides all the way to the C Suite. Well, meet Dr. Lucas Joppa. A former environmental and computer science researcher at MSR who was tapped in 2017 to become the company’s first Chief Environmental Scientist, Dr. Joppa is now the Chief Environmental Officer at Microsoft, another first, and is responsible for managing the company’s overall environmental sustainability efforts from operations to policy to technology.

Today, Dr. Joppa shares how his love for nature and the joy of discovery actually helped shape his career path, and tells us all about AI for Earth, a multi-year, multi-million dollar initiative to deploy the full scale of Microsoft’s products, policies and partnerships across four key areas of agriculture, water, biodiversity and climate, and transform the way society monitors, models, and ultimately manages Earth’s natural resources.

Dr. Marc Pollefeys is a Professor of Computer Science at ETH Zurich, a Partner Director of Science for Microsoft, and the Director of a new Microsoft Mixed Reality and AI lab in Switzerland. He’s a leader in the field of computer vision research, but it’s hard to pin down whether his work is really about the future of computer vision, or about a vision of future computers. Arguably, it’s both!

On today’s podcast, Dr. Pollefeys brings us up to speed on the latest in computer vision research, including his innovative work with Azure Spatial Anchors, tells us how devices like Kinect and HoloLens may have cut their teeth in gaming, but turned out to be game changers for both research and industrial applications, and explains how, while it’s still early days now, in the future, you’re much more likely to put your computer on your head than on your desk or your lap.

Ann Paradiso is an interaction designer and the Principal User Experience Designer for the NExT Enable group at Microsoft Research. She’s also the epitome of a phrase she often uses to describe other people: a force of nature. Together with a diverse array of team members and collaborators, many of whom have ALS or other conditions that affect mobility and speech, Ann works on new interaction paradigms for assistive technologies hoping to make a more bespoke approach to technology solutions accessible, at scale, to the people who need it most.

On today’s podcast, Ann tells us all about life in the extreme constraint design lane, explains what a PALS is, and tells us some incredibly entertaining stories about how the eye tracking technology behind the Eye Controlled Wheelchair and the Hands-Free Music Project has made its way from Microsoft’s campus to some surprising events around the country, including South by Southwest and Mardi Gras.

This episode first aired in September, 2018:

You may have heard the phrase, necessity is the mother of invention, but for Dr. Nicolo Fusi, a researcher at the Microsoft Research lab in Cambridge, Massachusetts, the mother of his invention wasn’t so much necessity as it was boredom: the special machine learning boredom of manually fine-tuning models and hyper-parameters that can eat up tons of human and computational resources, but bring no guarantee of a good result. His solution? Automate machine learning with a meta-model that figures out what other models are doing, and then predicts how they’ll work on a given dataset.

On today’s podcast, Dr. Fusi gives us an inside look at Automated Machine Learning – Microsoft’s version of the industry’s AutoML technology – and shares the story of how an idea he had while working on a gene editing problem with CRISPR/Cas9 turned into a bit of a machine learning side quest and, ultimately, a surprisingly useful instantiation of Automated Machine Learning – now a feature of Azure Machine Learning – that reduces dependence on intuition and takes some of the tedium out of data science at the same time.

If you’ve ever played video games, you know that for the most part, they look a lot better than they sound. That’s largely due to the fact that audible sound waves are much longer – and a lot more crafty – than visual light waves, and therefore, much more difficult to replicate in simulated environments. But Dr. Nikunj Raghuvanshi, a Senior Researcher in the Interactive Media Group at Microsoft Research, is working to change that by bringing the quality of game audio up to speed with the quality of game video. He wants you to hear how sound really travels – in rooms, around corners, behind walls, out doors – and he’s using computational physics to do it.

Today, Dr. Raghuvanshi talks about the unique challenges of simulating realistic sound on a budget (both money and CPU), explains how classic ideas in concert hall acoustics need a fresh take for complex games like Gears of War, reveals the computational secret sauce you need to deliver the right sound at the right time, and tells us about Project Triton, an acoustic system that models how real sound waves behave in 3-D game environments to makes us believe with our ears as well as our eyes.

When we think of information processing systems, we often think of computers, but we ourselves are made up of information processing systems – trillions of them – also known as the cells in our bodies. While these cells are robust, they’re also extraordinarily complex and not altogether predictable. Wouldn’t it be great, asks Dr. Andrew Phillips, head of the Biological Computation Group at Microsoft Research in Cambridge, if we could figure out exactly how these building blocks of life work and harness their power with the rigor and predictability of computer science? To answer that, he’s spent a good portion of his career working to develop a system of intelligence that can, literally, program biology.

Today, Dr. Phillips talks about the challenges and rewards inherent in reverse engineering biological systems to see how they perform information processing. He also explains what we can learn from stressed out bacteria, and tells us about Station B, a new end-to-end platform his team is working on that aims to reduce the trial and error nature of lab experiments and help scientists turn biological cells into super-factories that could solve some of the most challenging problems in medicine, agriculture, the environment and more.

This episode first aired in August of 2018.

You know those people who work behind the scenes to make sure nothing bad happens to you, and if they’re really good, you never know who they are because nothing bad happens to you? Well, meet one of those people. Dr. Brian LaMacchia is a Distinguished Engineer and he heads up the Security and Cryptography Group at Microsoft Research. It’s his job to make sure – using up-to-the-minute math – that you’re safe and secure online, both now, and in the post-quantum world to come.

Today, Dr. LaMacchia gives us an inside look at the world of cryptography and the number theory behind it, explains what happens when good algorithms go bad, and tells us why, even though cryptographically relevant quantum computers are still decades away, we need to start developing quantum-resistant algorithms right now.

If you’ve ever wondered why, in the age of the internet, we still don’t hold our elections online, you need to spend more time with Dr. Josh Benaloh, Senior Cryptographer at Microsoft Research in Redmond. Josh knows a lot about elections, and even more about homomorphic encryption, the mathematical foundation behind the end-to-end verifiable election systems that can dramatically improve election integrity today and perhaps move us toward wide-scale online voting in the future.

Today, Dr. Benaloh gives us a brief but fascinating history of elections, explains how the trade-offs among privacy, security and verifiability make the relatively easy math of elections such a hard problem for the internet, and tells the story of how the University of Michigan fight song forced the cancellation of an internet voting pilot.

Humans are unique in their ability to learn from, understand the world through and communicate with language… Or are they? Perhaps not for long, if Dr. Layla El Asri, a Research Manager at Microsoft Research Montreal, has a say in it. She wants you to be able to talk to your machine just like you’d talk to another person. That’s the easy part. The hard part is getting your machine to understand and talk back to you like it’s that other person.

Today, Dr. El Asri talks about the particular challenges she and other scientists face in building sophisticated dialogue systems that lay the foundation for talking machines. She also explains how reinforcement learning, in the form of a text game generator called TextWorld, is helping us get there, and relates a fascinating story from more than fifty years ago that reveals some of the safeguards necessary to ensure that when we design machines specifically to pass the Turing test, we design them in an ethical and responsible way.

If every question in life could be answered by choosing from just a few options, machine learning would be pretty simple, and life for machine learning researchers would be pretty sweet. Unfortunately, in both life and machine learning, things are a bit more complicated. That’s why Dr. Manik Varma, Principal Researcher at MSR India, is developing extreme classification systems to answer multiple-choice questions that have millions of possible options and help people find what they are looking for online more quickly, more accurately and less expensively.

On today’s podcast, Dr. Varma tells us all about extreme classification (including where in the world you might actually run into 10 or 100 million options), reveals how his Parabel and Slice algorithms are making high quality recommendations in milliseconds, and proves, with both his life and his work, that being blind need not be a barrier to extreme accomplishment.

Haiyan Zhang is a designer, technologist and maker of things (really cool technical things) who currently holds the unusual title of Innovation Director at the Microsoft Research lab in Cambridge, England. There, she applies her unusual skillset to a wide range of unusual solutions to real-life problems, many of which draw on novel applications of gaming technology in serious areas like healthcare.

On today’s podcast, Haiyan talks about her unique “brain hack” approach to the human-centered design process, and discusses a wide range of projects, from the connected play experience of Zanzibar, to Fizzyo, which turns laborious breathing exercises for children with cystic fibrosis into a video game, to Project Emma, an application of haptic vibration technology that, somewhat curiously, offsets the effects of tremors caused by Parkinson’s disease.

From his deep technical roots as a principal researcher and founder of the Communications, Collaboration and Signal Processing group at MSR, through his tenure as Managing Director of the lab in Redmond, to his current role as Distinguished Engineer, Chief Scientist for Microsoft Research and manager of the MSR NExT Enable group, Dr. Rico Malvar has seen – and pretty well done – it all.

Today, Dr. Malvar recalls his early years at a fledgling Microsoft Research, talks about the exciting work he oversees now, explains why designing with the user is as important as designing for the user, and tells us how a challenge from an ex-football player with ALS led to a prize winning hackathon project and produced the core technology that allows you to type on a keyboard without your hands and drive a wheelchair with your eyes.

You never know how an incident in your own life might inspire a breakthrough in science, but Dr. Cecily Morrison, a researcher in the Human Computer Interaction group at Microsoft Research Cambridge, can attest to how even unexpected events can cause us to see things through a different – more inclusive – lens and, ultimately, give rise to innovations in research that impact everyone.

On today’s podcast, Dr. Morrison gives us an overview of what she calls the “pillars” of inclusive design, shares how her research is positively impacting people with health issues and disabilities, and tells us how having a child born with blindness put her in touch with a community of people she would otherwise never have met, and on the path to developing Project Torino, an inclusive physical programming language for children with visual impairments.

The entertainment industry has long offered us a vision of the perfect personal assistant: one that not only meets our stated needs but anticipates needs we didn’t even know we had. But these uber-assistants, from the preternaturally prescient Radar O’Reilly in the TV show M.A.S.H. to Tony Stark’s digital know-and-do-it-all Jarvis in Iron Man, have always lived in the realm of fiction or science fiction. That could all change, if Dr. Paul Bennett, Principal Researcher and Research Manager of the Information and Data Sciences group at Microsoft Research, has anything to say about it. He and his team are working to make machines “calendar and email aware,” moving intelligent assistance into the realm of science and onto your workstation.

Today, Dr. Bennett brings us up to speed on the science of contextually intelligent assistants, explains how what we think our machines can do actually shapes what we expect them to do, and shares how current research in machine learning and data science is helping machines reason on our behalf in the quest to help us find the right information effortlessly.

When people first started making software, computers were relatively rare and there was no internet, so programming languages were designed to get the job done quickly and run efficiently, with little thought for security. But software is everywhere now, from our desktops to our cars, from the cloud to the internet of things. That’s why Dr. Jonathan Protzenko, a researcher in the RiSE – or Research in Software Engineering – group at Microsoft Research, is working on designing better software tools in order to make our growing software ecosystem safer and more secure.

Today, Dr. Protzenko talks about what’s wrong with software (and why it’s vitally important to get it right), explains why there are so many programming languages (and tells us about a few he’s been working on), and finally, acts as our digital Sherpa for Project Everest, an assault on software integrity and confidentiality that aims to build and deploy a verified HTTPS stack.

The episode first aired in May, 2018.
In the world of machine learning, there’s been a notable trade-off between accuracy and intelligibility. Either the models are accurate but difficult to make sense of, or easy to understand but prone to error. That’s why Dr. Rich Caruana, Principal Researcher at Microsoft Research, has spent a good part of his career working to make the simple more accurate and the accurate more intelligible.

Today, Dr. Caruana talks about how the rise of deep neural networks has made understanding machine predictions more difficult for humans, and discusses an interesting class of smaller, more interpretable models that may help to make the black box nature of machine learning more transparent.

This episode first aired in January, 2018.
When we look at a skyscraper or a suspension bridge, a simple search engine box on a screen looks tiny by comparison. But Dr. Simon Peyton Jones would like to remind us that computer programs, with hundreds of millions of lines of code, are actually among the largest structures human beings have ever built. A principle researcher at the Microsoft Research Lab in Cambridge, England, co-developer of the programming language Haskell, and a Fellow of Britain’s Royal Society, Simon Peyton Jones has dedicated his life to this very particular kind of construction work.

Today, Dr. Peyton Jones shares his passion for functional programming research, reveals how a desire to help other researchers write and present better turned him into an unlikely YouTube star, and explains why, at least in the world of programming languages, purity is embarrassing, laziness is cool, and success should be avoided at all costs.

This episode first aired in March, 2018.
Learning to read, think and communicate effectively is part of the curriculum for every young student. But Dr. Adam Trischler, Research Manager and leader of the Machine Comprehension team at Microsoft Research Montreal, would like to make it part of the curriculum for your computer as well. And he’s working on that, using methods from machine learning, deep neural networks, and other branches of AI to close the communication gap between humans and computers.

Today, Dr. Trischler talks about his dream of making literate machines, his efforts to design meta-learning algorithms that can actually learn to learn, the importance of what he calls “few-shot learning” in that meta-learning process, and how, through a process of one-to-many mapping in machine learning, our computers not may not only be answering our questions, but asking them as well.

Amos Miller is a product strategist on the Microsoft Research NeXT Enable team, and he’s played a pivotal role in bringing some of MSR’s most innovative research to users with disabilities. He also happens to be blind, so he can appreciate, perhaps in ways others can’t, the value of the technologies he works on, like Soundscape, an app which enhances mobility independence through audio and sound.

On today’s podcast, Amos Miller answers burning questions like how do you make a microwave accessible, what’s the cocktail party effect, and how do you hear a landmark? He also talks about how researchers are exploring the untapped potential of 3D audio in virtual and augmented reality applications, and explains how, in the end, his work is not so much about making technology more accessible, but using technology to make life more accessible.

Dr. Sebastien Bubeck is a mathematician and a senior researcher in the Machine Learning and Optimization group at Microsoft Research. He’s also a self-proclaimed “bandit” who claims that, despite all the buzz around AI, it’s still a science in its infancy. That’s why he’s devoted his career to advancing the mathematical foundations behind the machine learning algorithms behind AI.

Today, Dr. Bubeck explains the difficulty of the multi-armed bandit problem in the context of a parameter- and data-rich online world. He also discusses a host of topics from randomness and convex optimization to metrical task systems and log n competitiveness to the surprising connection between Gaussian kernels and what he calls some of the most beautiful objects in mathematics.

Dr. Christopher Bishop is quite a fellow. Literally. Fellow of the Royal Academy of Engineering. Fellow of Darwin College in Cambridge, England. Fellow of the Royal Society of Edinburgh. Fellow of The Royal Society. Microsoft Technical Fellow. And one of the nicest fellows you’re likely to meet! He’s also Director of the Microsoft Research lab in Cambridge, where he oversees a world-class portfolio of research and development endeavors in machine learning and AI.

Today, Dr. Bishop talks about the past, present and future of AI research, explains the No Free Lunch Theorem, talks about the modern view of machine learning (or how he learned to stop worrying and love uncertainty), and tells how the real excitement in the next few years will be the growth in our ability to create new technologies not by programming machines but by teaching them to learn.

This episode first aired in March (2018)
One of the most intriguing areas of machine learning research is affective computing, where scientists are working to bridge the gap between human emotions and computers. It is here, at the intersection of psychology and computer science, that we find Dr. Daniel McDuff, who has been designing systems, from hardware to algorithms, that can sense human behavior and respond to human emotions.

Today, Dr. McDuff talks about why we need computers to understand us, outlines the pros and cons of designing emotionally sentient agents, explains the technology behind CardioLens, a pair of augmented reality glasses that can take your heartrate by looking at your face, and addresses the challenges of maintaining trust and privacy when we’re surrounded by devices that want to know not just what we’re doing, but how we’re feeling.

After decades of research in processing audio signals, we’ve reached the point of so-called performance saturation. But recent advances in machine learning and signal processing algorithms have paved the way for a revolution in speech recognition technology and audio signal processing. Dr. Ivan Tashev, a Partner Software Architect in the Audio and Acoustics Group at Microsoft Research, is no small part of the revolution, having both published papers and shipped products at the forefront of the science of sound.

On today’s podcast, Dr. Tashev gives us an overview of the quest for better sound processing and speech enhancement, tells us about the latest innovations in 3D audio, and explains why the research behind audio processing technology is, thanks to variations in human perception, equal parts science, art and craft.

In 1998, Microsoft Research opened a small lab in Beijing to expand its research efforts and draw on the immense high-tech talent pool in China. No one expected that only twenty years later, MSR Asia would become the dynamic organization it is today, with innovative research contributing to nearly every part of Microsoft’s business. Dr. Hsiao-Wuen Hon has watched it grow from the beginning and this year, celebrates the lab’s 20th anniversary as Managing Director, Corporate Vice President and Chairman of Microsoft’s Asia-Pacific R&D Group.

On today’s podcast, Dr. Hon gives us a brief history of MSR Asia, from its humble beginnings to its significant role in the AI boom today, talks about MSR Asia’s unique talent pipeline, shares his vision for the complementary roles of machine intelligence and human wisdom, and explains why, he believes, the more progress we make in AI, the better we understand ourselves.

As traditional semiconductor technologies for computer storage scale down, everyone is looking for alternative solutions to the growing gap between the amount of data we’re capable of producing and the amount of data we’re capable of storing. While some have focused on hardware accelerators for machine learning, and others are investigating new memory technologies, Dr. Karin Strauss, a Senior Researcher at Microsoft Research in Redmond, has been exploring the role of biotechnology in IT via an end-to-end system that stores digital data in DNA.

On today’s podcast, Dr. Strauss talks about life at the intersection of computer science and biology which, for many, is more like the intersection of science fiction and science, and explains how the unique properties of DNA could eventually enable us to store really big data in really small places for a really long time.

The ancient Chinese philosopher Confucius famously exhorted his pupils to study the past if they would divine the future. In 2018, we get the same advice from a decidedly more modern, but equally philosophical Bill Buxton, Principal Researcher in the HCI group at Microsoft Research. In addition to his pioneering work in computer science and design, Bill Buxton has spent the past several decades amassing a collection of more than a thousand artifacts that chronicle the history of human computer interaction for the very purpose of informing the future of human computer interaction.

Today, in a wide-ranging interview, Bill Buxton explains why Marcel Proust and TS Eliot can be instructive for computer scientists, why the long nose of innovation is essential to success in technology design, why problem-setting is more important than problem-solving, and why we must remember, as we design our technologies, that every technological decision we make is an ethical decision as well.

2018 marks the 10th anniversary of Microsoft Research New England in Cambridge, Massachusetts, so it’s the perfect time to talk with someone who was there from the lab’s beginning: Technical Fellow, Managing Director and Co-founder, Dr. Jennifer Chayes. But not only does Dr. Chayes run the New England lab of MSR, she also directs two other highly renowned, interdisciplinary research labs in New York City and Montreal, Quebec. Add to that a full slate of personal research projects and service on numerous boards, committees and foundations, and you’ve got one of the busiest and most influential women in high tech.

On today’s podcast, Dr. Chayes shares her passion for the value of undirected inquiry, talks about her unlikely journey from rebel to researcher, and explains how she believes her research philosophy – more botanist than boss – prepares the fertile ground necessary for important, innovative and impactful research.

Asta Roseway has a formal title. It’s Principal Research Designer in the HCI group at Microsoft Research. But she’s also been described as a conductor, an alchemist, a millennial in a Gen-Xer’s body and, in her own words, a fusionist. What’s a fusionist, you might ask? Well, you’re about to find out.

On today’s podcast, Asta gives an inside look at one of the most unconventional labs at Microsoft Research. Located at the intersection of science, technology and art, it’s a lab that insists that technology, like art, should push boundaries, tell stories and feed our souls. Get ready for the unexpected because when Asta asks “what if?” you’re likely to find yourself immersed in a world of responsive clothing, smart tattoos, talking plants and even environmentally sensitive… makeup!

You may have heard the phrase, necessity is the mother of invention, but for Dr. Nicolo Fusi, a researcher at the Microsoft Research lab in Cambridge, MA, the mother of his invention wasn’t so much necessity as it was boredom: the special machine learning boredom of manually fine-tuning models and hyper-parameters that can eat up tons of human and computational resources, but bring no guarantee of a good result. His solution? Automate machine learning with a meta-model that figures out what other models are doing, and then predicts how they’ll work on a given dataset.

On today’s podcast, Dr. Fusi gives us an inside look at Automated Machine Learning – Microsoft’s version of the industry’s AutoML technology – and shares the story of how an idea he had while working on a gene editing problem with CRISPR/Cas9 turned into a bit of a machine learning side quest and, ultimately, a surprisingly useful instantiation of Automated Machine Learning - now a feature of Azure Machine Learning - that reduces dependence on intuition and takes some of the tedium out of data science at the same time.

At the heart of any vibrant research community, you’ll find a diverse range of scientists. You’re also likely to find a robust internship program, like the one at Microsoft Research. This summer, MSR welcomed another stellar group of interns who had the opportunity to learn, collaborate, and network with colleagues and mentors who will impact their lives for years to come.

On today’s podcast, you’ll hear the stories of three of these interns, each of whom came to Microsoft Research from a different field, with a different story and a different perspective, but all of whom share MSR’s passion for finding innovative solutions to the world’s toughest challenges.

Dr. Nancy Baym is a communication scholar, a Principal Researcher in MSR’s Cambridge, Massachusetts, lab, and something of a cyberculture maven. She’s spent nearly three decades studying how people use communication technologies in their everyday relationships and written several books on the subject. The big take away? Communication technologies may have changed drastically over the years, but human communication itself? Not so much.

Today, Dr. Baym shares her insights on a host of topics ranging from the arduous maintenance requirements of social media, to the dialectic tension between connection and privacy, to the funhouse mirror nature of emerging technologies. She also talks about her new book, Playing to the Crowd: Musicians, Audiences and the Intimate Work of Connection, which explores how the internet transformed – for better and worse – the relationship between artists and their fans.

Datacenters have a hard time keeping their cool. Literally. And with more and more datacenters coming online all over the world, calls for innovative solutions to “cool the cloud” are getting loud. So, Ben Cutler and the Special Projects team at Microsoft Research decided to try to beat the heat by using one of the best natural venues for cooling off on the planet: the ocean. That led to Project Natick, Microsoft’s prototype plan to deploy a new class of eco-friendly datacenters, under water, at scale, anywhere in the world, from decision to power-on, in 90 days. Because, presumably for Special Projects, go big or go home.

In today’s podcast we find out a bit about what else the Special Projects team is up to, and then we hear all about Project Natick and how Ben and his team conceived of, and delivered on, a novel idea to deal with the increasing challenges of keeping datacenters cool, safe, green, and, now, dry as well!

The wildly popular video game, Minecraft, might appear to be an unlikely candidate for machine learning research, but to Dr. Katja Hofmann, the research lead of Project Malmo in the Machine Intelligence and Perception Group at Microsoft Research in Cambridge, England, it’s the perfect environment for teaching AI agents, via reinforcement learning, to act intelligently – and cooperatively – in the open world.

Today, Dr. Hofmann talks about her vision of a future where machines learn to collaborate with people and empower them to help solve complex, real-world problems. She also shares the story of how her early years in East Germany, behind the Iron Curtain, shaped her both personally and professionally, and ultimately facilitated a creative, exploratory mindset about computing that informs her work to this day.

You know those people who work behind the scenes to make sure nothing bad happens to you, and if they’re really good, you never know who they are because nothing bad happens to you? Well, meet one of those people. Dr. Brian LaMacchia is a Distinguished Engineer and he heads up the Security and Cryptography Group at Microsoft Research. It’s his job to make sure – using up-to-the-minute math – that you’re safe and secure online, both now, and in the post-quantum world to come.

Today, Dr. LaMacchia gives us an inside look at the world of cryptography and the number theory behind it, explains what happens when good algorithms go bad, and tells us why, even though cryptographically relevant quantum computers are still decades away, we need to start developing quantum-resistant algorithms right now.

If your idea of a great job includes pursuing untethered research, shepherding brilliant researchers and helping shape the long-term strategy of one of the largest tech companies in the world… oh, and also publishing prolifically, authoring patents, winning awards and speaking around the world… you are in good company. That’s what Dr. Victor Bahl, Distinguished Scientist and Director of Mobility and Networking at Microsoft Research, does for a living. And he loves it!

Today, in our first live podcast, recorded at MSR’s 2018 Faculty Summit, Dr. Bahl shares some fascinating stories from his long and illustrious career, gives us an inside look at what’s new in networking, and, explains why, in an industry where it pays to be the smartest person in the room, it’s important to be a world-class listener.

Kevin Scott has embraced many roles over the course of his illustrious career in technology: software developer, engineering executive, researcher, angel investor, philanthropist, and now, Chief Technology Officer of Microsoft. But perhaps no role suits him so well – or has so fundamentally shaped all the others – as his self-described role of “all-around geek.”

Today, in a wide-ranging interview, Kevin shares his insights on both the history and the future of computing, talks about how his impulse to celebrate the extraordinary people “behind the tech” led to an eponymous non-profit organization and a podcast, and… reveals the superpower he got when he was in grad school.

Dr. Lenin Ravindranath Sivalingam is a researcher by trade, but by nature, he’s an entrepreneur, and a hacker with a heart of gold. It’s this combination of skill and passion that informs his work at Microsoft Research, driving him to discover and build tools that will make life both easier for developers and better for end-users.

Today, Dr. Ravindranath Sivalingam tells us why he is so passionate about what he does, explains how internships can literally change your life, and shares the story of how a hackathon idea turned into a prize-winning project… and then became the backbone of a powerhouse tool for gamers and their fans.

To learn more about Dr. Ravindranath Sivalingam, and how Microsoft researchers are working to make life more easier and more robust for everyone, visit Microsoft.com/research

First aired on January 17, 2018. If someone mentions quantum computing, and you find yourself outwardly nodding your head, but secretly shaking it, you’re in good company: some of the world’s smartest people admit they don’t really understand it either. Fortunately, some of the world’s other smartest people, like Dr. Krysta Svore, Principal Research Manager of the Microsoft Quantum – or QuArC – group at Microsoft Research in Redmond, actually DO understand quantum computing, and are working hard to make it a reality.

Today, Dr. Svore shares her passion for quantum algorithms and their potential to solve some of the world’s biggest problems, explains why Microsoft’s topological quantum bit – or qubit – is a game changer for quantum computing, and assures us that, although qubits live in dilution refrigerators at temperatures near absolute zero, quantum researchers can still sit in the comfort of their offices and work with the computer programmer’s equivalent of Schroedinger’s Cat.

First aired on December 4th, 2017. When it comes to artificial intelligence, Dr. Eric Horvitz is as passionate as he is accomplished. His contributions to the field, and service on the boards of nearly every technical academy and association in the country, have earned him the respect – and awe – of his colleagues, along with the position of Technical Fellow and Managing Director of Microsoft Research. Dr. Horvitz talks about the goal of artificial intelligence, his vision for our collaborative future with machines, what we can learn from the Wright brothers, and how a short stint of “six months, maximum” became an illustrious and, in his words, joyful, 25-year career at Microsoft Research.

This episode first aired in January (2018).
In an era of AI breakthroughs and other exciting advances in computer science, Dr. Ben Zorn would like to remind us that behind every great technical revolution is… a programming language. As a Principal Researcher and the Co-director of RiSE – or Research in Software Engineering – group at Microsoft Research, Dr. Zorn has dedicated his life to making sure the software that now touches nearly everything in our lives is easy, accurate, reliable and secure. Today, Dr. Zorn tells us some great stories about bugs and whales, warns us against the dumb side of “smart” objects, shares about his group’s attempt to scale the Everest of software security, and makes a great case that the most important programming language in the world today is… the spreadsheet.

This episode first aired in April (2018).
When we think about artificial intelligence and the “world of the future,” our vision is usually more Jetsons than Green Acres. But for Dr. Ranveer Chandra, a Principal Researcher in the Systems and Networking group at Microsoft Research, rural farms are the perfect place to realize the benefits of AI through what he calls precision agriculture, or data-driven farming.

Today, in a wide-ranging interview, Dr. Chandra talks about how his research may eventually make your wi-fi signal stronger and your battery life longer, but also shares the story of how spending childhood summers with his grandparents in rural India inspired a line of research that could change the face of farming and help meet the food and nutrition needs of a growing global population.

Developing complex artificial intelligence systems in a lab is a challenging task, but what happens when they go into production and interact with real humans? That’s what researchers like Dr. Fernando Diaz, a Principal Research Manager at Microsoft Research Montreal, want to know. He and his colleagues are trying to understand – and address – the social implications of these systems as they enter the open world.

Today, Dr. Diaz shares his insights on the kinds of questions we need to be asking about artificial intelligence and its impact on society. He also talks about how algorithms can affect your taste in music, and why now, more than ever, computer science education needs to teach ethics along with algorithms.

This episode first aired in November (2017). Dr. Jaime Teevan has a lot to say about productivity in a fragmented culture, and some solutions that seem promising, if somewhat counter-intuitive. Dr. Teevan is a Microsoft researcher, University of Washington Affiliate Professor, and the mother of four young boys. Today she talks about what she calls the productivity revolution, and explains how her research in micro-productivity – making use of short fragments of time to help us accomplish larger tasks -  could help us be more productive, and experience a better quality of life at the same time.

In technical terms, computer vision researchers “build algorithms and systems to automatically analyze imagery and extract knowledge from the visual world.” In layman’s terms, they build machines that can see. And that’s exactly what Principal Researcher and Research Manager, Dr. Gang Hua, and Computer Vision Technology team, are doing. Because being able to see is really important for things like the personal robots, self-driving cars, and autonomous drones we’re seeing more and more in our daily lives.

Today, Dr. Hua talks about how the latest advances in AI and machine learning are making big improvements on image recognition, video understanding and even the arts. He also explains the distributed ensemble approach to active learning, where humans and machines work together in the lab to get computer vision systems ready to see and interpret the open world.

When we think of medals, we usually picture them over the pocket of a military hero, not over the pocket protector of a computer scientist. That may be because not many academics end up working with the Department of Defense. But Dr. Chris White, now a Principal Researcher at Microsoft Research, has, and he’s received several awards for his efforts in fighting terrorism and crime with big data, statistics and machine learning.

Today, Dr. White talks about his “problem-first” approach to research, explains the vital importance of making data understandable for everyone, and shares the story of how a one-week detour from academia turned into an extended tour in Afghanistan, a stint at DARPA, and, eventually, a career at Microsoft Research.

In the world of machine learning, there’s been a notable trade-off between accuracy and intelligibility. Either the models are accurate but difficult to make sense of, or easy to understand but prone to error. That’s why Dr. Rich Caruana, Principal Researcher at Microsoft Research, has spent a good part of his career working to make the simple more accurate and the accurate more intelligible.

Today, Dr. Caruana talks about how the rise of deep neural networks has made understanding machine predictions more difficult for humans, and discusses an interesting class of smaller, more interpretable models that may help to make the black box nature of machine learning more transparent.

With 7 billion people on the planet, you might be surprised to learn that approximately a billion of those people experience some form of disability. Enter Principal Researcher and Research Manager, Dr. Merrie Ringel Morris, and the Ability Group at Microsoft Research. They’re working to remove accessibility barriers both to and through technology, empowering people with disabilities to better perform their daily tasks.

Today, Dr. Morris gives us some fascinating insights into the world of “ability,” talks about how technology is augmenting not only sensory and motor abilities, but cognitive and social abilities as well, and shares how Microsoft, through its AI for Accessibility initiative, is committed to extending the capabilities and enhancing the quality of life for every person on the planet.

Humans are wired to communicate, but we don’t always understand each other. Especially when we don’t speak the same language. But Arul Menezes, the Partner Research Manager who heads MSR’s Machine Translation team, is working to remove language barriers to help people communicate better. And with the help of some innovative machine learning techniques, and the combined brainpower of machine translation, natural language and machine learning teams in Redmond and Beijing, it’s happening sooner than anyone expected.

Today, Menezes talks about how the advent of deep learning has enabled exciting advances in machine translation, including applications for people with disabilities, and gives us an inside look at the recent “human parity” milestone at Microsoft Research, where machines translated a news dataset from Chinese to English with the same accuracy and quality as a person.

Some of the world’s leading architects are people that you’ve probably never heard of, and they’ve designed and built some of the world’s most amazing structures that you’ve probably never seen. Or at least you don’t think you have. One of these architects is Dr. Doug Burger, Distinguished Engineer at Microsoft Research NExT. And, if you use a computer, or store anything in the Cloud, you’re a beneficiary of the beautiful architecture that he, and people like him, work on every day.

Today, in a fast-paced interview, Dr. Burger talks about how advances in AI and deep machine learning have placed new acceleration demands on current hardware and computer architecture, offers some observations about the demise of Moore’s Law, and shares his vision of what life might look like in a post-CPU, post-von-Neumann computing world.

Autonomous flying agents – or flying robots – may seem like the stuff of sci-fi to the average person, but to Dr. Ashish Kapoor, Principal Researcher and Research Manager of the Aerial Informatics and Robotics Group at Microsoft Research, they’re much closer to science than to fiction. And, having built – and flight tested – his own airplane, complete with state-of-the-art avionics designed to run AI and ML algorithms, he has the street cred – or should we say flight cred – to prove it.

Today, Dr. Kapoor talks about how cutting-edge machine learning techniques are empowering a new generation of autonomous vehicles, and tells us all about AirSim, an innovative platform that’s helping bridge the simulator-to-reality gap, paving the way for safer, more robust real-world AI systems of all kinds

Teaching computers to read, think and communicate like humans is a daunting task, but it’s one that Dr. Geoff Gordon embraces with enthusiasm and optimism. Moving from an academic role at Carnegie Mellon University, to a new role as Research Director of the Microsoft Research Lab in Montreal, Dr. Gordon embodies the current trend toward the partnership between academia and industry as we enter what many believe will be a new era of progress in machine learning and artificial intelligence.

Today, Dr. Gordon gives us a brief history of AI, including his assessment of why we might see a break in the weather-pattern of AI winters, talks about how collaboration is essential to innovation in machine learning, shares his vision of the mindset it takes to tackle the biggest questions in AI, and reveals his life-long quest to make computers less… well, less computer-like.

Emotions are fundamental to human interaction, but in a world where humans are increasingly interacting with AI systems, Dr. Mary Czerwinski, Principal Researcher and Research Manager of the Visualization and Interaction for Business and Entertainment group at Microsoft Research, believes emotions may be fundamental to our interactions with machines as well. And through her team’s work in affective computing, the quest to bring Artificial Emotional Intelligence – or AEI – to our computers may be closer than we think.

Today, Dr. Czerwinski tells us how a cognitive psychologist found her way into the research division of the world’s largest software company, suggests that rather than trying to be productive 24/7, we should aim for Emotional Homeostasis instead, and tells us how, if we do it right, our machines could become a sort of “emotional at-work DJ,” sensing and responding to our emotional states, and helping us to become happier and more productive at the same time.

From ancient hieroglyphics to secret decoder rings to World War II Enigma code-makers and code-breakers, cryptography has always held a particular fascination for us. But few of us have the skills – or can actually do the math – to unlock the mysteries of encrypted data. Fortunately, Dr. Kristin Lauter, distinguished mathematician, founder of the Women in Numbers Network, and Principal Researcher and Research Manager for the Cryptography Group at Microsoft Research, can. And she is using her powers for good, not for evil!

Today, Dr. Lauter tells us why she feels lucky  to do math for a living, explains the singular beauty of elliptic curves and the singular difficulty of supersingular isogeny graphs, talks about how homomorphic encryption – part of the field of Private AI – allows us to operate on, while still protecting, our most sensitive data, and shares her dream of one day, seeing a Grace Hopper-like conference to celebrate women in mathematics.