UC Berkeley
Fall 2020
STAT 210A Theoretical Statistics, by Will Fithian.
PH 240B Biostatistical Methods: Survival Analysis and Causality, by Mark van der Laan.
PH 240C Biostatistical Methods: Computational Statistics with Application in Biology and Medicine, by Jingshen Wang.
Spring 2021
STAT 210B Theoretical Statistics, by Martin Wainwright. (with A+ grading)
PH 240A Introduction to Modern Biostatistical Theory and Practice, by Mark van der Laan and Jingshen Wang.
PH 252D Introduction to Causal Inference, by Maya Peterson.
Fall 2021
STAT 256 Causal inference, by Peng Ding. (with A+ grading)
STAT 150 Stochastic process, by Benson Au.
CS 285 Reinforcement learning, by Sergey Levine.
EE 227BT Convex optimization, by Somayeh Sojoudi and Laurent El Ghaoui.
STAT 278B Neyman Seminar, by Song Mei.
Spring 2022
EECS 227C Convex optimization and approximation, by Jiantao Jiao.
PH 292 Biostatistic thesis, by Corinne Riddell.
STAT 155 Game theory, by Adam Lucas. (Auditing)
Fall 2022
Wish list
See here for my wish list.
There are topics I want to learn:
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Minimax theory
Semiparametric theory
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