Courses

University of California, Berkeley

• Spring 2024

  • STAT 260: Non-stationary Dynamics (audited), by Prof. Vadim Gorin

• Spring 2023

  • COMPSCI 267: Applications of Parallel Computers, by Prof. Aydin Buluc, Jim Demmel and Laura Grigori

• Spring 2022

  • STAT 248: Analysis of Time Series, by Prof. Adityanand Guntuboyina

• Fall 2021

  • CS 285: Deep Reinforcement Learning, by Prof. Sergey Levine

  • EE 229A: Information Theory and Coding, by Prof. Venkatacha Anantharam

• Spring 2021

  • STAT 210B: Theoretical Statistics, by Prof. Martin Wainwright

  • STAT 205B: Probability Theory, by Prof. James Pitman

• Fall 2020

  • STAT 205A: Probability Theory, by Prof. Shirshendu Ganguly

  • STAT 210A: Theoretical Statistics, by Prof. William Fithian

• Spring 2020

  • MATH 228B: Numerical Solutions of Differential Equations, by Prof. Suncica Canic

  • ELENG 227C: Convex Optimization and Approximation, by Prof. Martin Wainwright

  • IEOR 269: Integer Programming and Combinatorial Optimization, by Prof. Alper Atamturk

• Fall 2019

  • MATH 228A: Numerical Solutions of Differential Equations, by Prof. Lin Lin

  • ELENG 227B: Convex Optimization, by Prof. Laurent El Ghaoui and Somayeh Sojoudi

  • COMPSCI 289A: Introduction to Machine Learning, by Prof. Stella Yu and Jennifer Listgarten

  • COMPSCI 282A: Designing, Visualizing and Understanding Deep Neural Networks (audited online), by Prof. John Canny

Peking University

Math Courses

• Fall 2018

  • Functional Analysis II

  • Topology (audited)

  • Numerical Solution of Partial Differential Equations (audited)

• Spring 2017

  • Introduction to Numerical Analysis

  • Algorithms for Big Data Analysis

  • Optimization Methods

• Fall 2017

  • Numerical Algebra

  • Applied Partial Differential Equations

  • Introduction to Stochastic Processes (Honor)

  • Methods of Stochastic Simulations (Applied Stochastic Analysis)

• Spring 2017

  • Ordinary Differential Equations

  • Probability Theory

  • Theory of Functions of Complex Variables

  • Mathematical Modeling

  • Functional Analysis I

• Fall 2016

  • Mathematical Analysis (Honor) III

  • Abstract Algebra

  • Functions of Real Variables

  • General Physics II

• Spring 2016

  • Mathematical Analysis (Honor) II

  • Advanced Algebra (Honor) II

  • General Physics I

• Fall 2015

  • Mathematical Analysis (Honor) I

  • Advanced Algebra (Honor) I

  • Geometry

Computer Science Courses

• Spring 2019

  • Software Engineering

  • Elementary Number Theory and Its Applications

  • Empirical Methods in Natural Language Processing

• Fall 2019

  • Principle of Microcomputer (B)

  • Human-Computer Interaction (HCI)

  • Game Theory

  • Principle of Programming Languages

• Spring 2018

  • Deep Learning: Algorithms and Applications

  • Introduction to Computer Networks

  • Networking Technology and Practices

• Fall 2017

  • Statistical Learning

  • Mathematical Logic

  • Web Software Technology

• Spring 2017

  • Introduction to Database Systems

  • Java Programming Language

  • Discrete Math II (Algebraic Structure and Combinatorial Mathematics)

• Fall 2016

  • Data Structure and Algorithm (B)

  • Discrete Math I (Set Theory and Graph Theory)

  • Operating Systems (B)

  • C++ Programming Language

• Spring 2016

  • Introduction to Computing (C Programming Language)