Toru Shirakawa, M.D., is an incoming Ph.D. student in Computational Precision Health at UC Berkeley and UCSF, mentored by Mark van der Laan. He develops longitudinal causal inference algorithms to optimize chronic disease management and promote healthy longevity. His recent work enhances longitudinal targeted learning with deep neural networks.
Mingxun Wang is currently an MA student in Biostatistics at the University of California, Berkeley, mentored by Mark van der Laan and Alejandro Schuler. His research interests primarily lie in TMLE, HAL, and Semiparametric Inference, with a focus on analyzing the theoretical properties of the estimators. His other research interests include Nonparametric statistics, Empirical Process, Percolation, Optimal Transport, and Manifolds. He is looking forward to exploring the applications of his research in various fields.
Wenxin Zhang is a PhD student in Biostatistics at UC Berkeley, working with Prof. Mark van der Laan. His research interests lie in the intersection of causal inference, machine learning, and semi-parametric estimation. He is also interested in adaptive designs.
