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  Mark on twitter: @mark_vdlaan Follow along on Twitter: The American Journal of Epidemiology: @AmJEpi Ellie: @EpiEllie Lucy: @LucyStats 🎶 Our intro/outro music is courtesy of Joseph McDade Edited by Cameron Bopp