Mark van der Laan is a professor of statistics at the University of California, Berkeley. His research focuses on developing statistical methods to estimate causal and non-causal parameters of interest, based on potentially complex and high dimensional data from randomized clinical trials or observational longitudinal studies, or from cross-sectional studies.
Center for Targeted Learning, Berkeley: https://ctml.berkeley.edu/
A causal roadmap: https://pubmed.ncbi.nlm.nih.gov/37900353/
Short course on causal learning: https://ctml.berkeley.edu/introduction-causal-inference
Handbook on the TLverse (Targeted Learning in R): https://ctml.berkeley.edu/publications/targeted-learning-handbook-causal-machine-learning-and-inference-tlverse-r-software
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