Current Teaching
- No teaching at SNU during 2023. (I am on sabbatical.)
Upcoming Teaching
- Machine Learning Theory, Spring 2024.
- Mathematical Foundations of Deep Neural Networks (심층신경망의 수학적 기초), M1407.001200, Spring 2024.
Past Teaching
- Mathematical Foundations of Deep Neural Networks (심층신경망의 수학적 기초), M1407.001200, Fall 2022.
- Mathematical and Numerical Optimization (최적화의 수학적 이론 및 계산), 3341.454, Fall 2022.
- Mathematical algorithms II (수학적 알고리즘 2), M1407.000500, Fall 2022.
- Topics in Applied Mathematics: Infinitely Large Neural Networks (응용수학특강: 심층신경망의 수학적 극한), 3341.751, Spring 2022.
- Large-Scale Convex Optimization: Algorithms and Analyses via Monotone Operators (Stanford), EE 392F, Spring 2023.
- Mathematical Foundations of Deep Neural Networks (심층신경망의 수학적 기초), M1407.001200, Fall 2021.
- Mathematical and Numerical Optimization (최적화의 수학적 이론 및 계산), 3341.454, Fall 2021.
- Mathematical algorithms I (수학적 알고리즘 1), M1407.000400, Spring 2021.
- Mathematical and Numerical Optimization (최적화의 수학적 이론 및 계산), 3341.454, Fall 2020.
- Mathematical Modeling and Simulation (수학적 모델링 및 전산실험), 3341.453, Spring 2020.
- Matrix Analysis for Scientists and Engineers, ECE205A (UCLA)
- A First Course on Large-Scale Optimization Methods, Math 285J (UCLA)
- Introduction to Programming, PIC10A (UCLA)
- Python with Applications, PIC16 (UCLA)
- Principles of Java Language with Applications, PIC20A (UCLA)
- Convex Optimization, EE 364A (Stanford)