Course
Coursework and Teaching
2018 Fall
MATH 222A: Partial Differential Equations
MATH 228A: Numerical Solution of Differential Equations
EE 227B: Convex Optimization
EE 290: Machine Learning for Sequential Decision Making Under Uncertainty
2019 Spring
EE 227C: Optimization for Modern Data Analysis (Auditing)
MATH 222B: Partial Differential Equations
MATH 228B: Numerical Solution of Differential Equations
STAT 205B: Probability Theory
2019 Fall
CS 281A: Statistical learning theory
CS 285: Deep reinforcement learning
CS 287: Advanced robotics (Auditing)
INDENG 223: Financial engineering system
2020 Spring
CS 294-158: Deep unsupervised learning
MATH 219: Dynamical system (Auditing)
Qualifying Exam: Syllabus
2020 Fall
EE 290: Population Games
EE 290: High-Dimensional Data Analysis with Low-Dimensional Models
STAT 210A: Theoretical statistics
MATH 170: Mathematical Methods for Optimization (GSI)
2021 Spring
EE 290: Theory of Multi-armed Bandits and Reinforcement Learning
STAT 210B: Theoretical Statistics
STAT 240: Robust and Nonparametric Statistics
MATH 195: Calculus of Variation and Optimal Control (GSI)