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)