teaching
Courses taught at SKKU, Chonnam National University, Yonsei, and K-MOOC.
Financial Engineering
- Basic Financial Mathematics, Sungkyunkwan University, Spring 2025
- Financial Mathematics (graduate), Sungkyunkwan University, Spring 2024–2025, Fall 2026, Fall 2027–2028 (scheduled)
- Advanced Financial Mathematics (graduate), Sungkyunkwan University, Fall 2025, Spring 2028 (scheduled)
- AI for Financial Engineering, K-MOOC, Winter 2021
- Financial Derivatives, Chonnam National University (CNU), Fall 2020
- Financial Statistics, Chonnam National University (CNU), Spring 2020–2023
- Basic Financial Mathematics, Chonnam National University (CNU), Spring 2020
- Mathematics in Financial Society, Yonsei University, Fall 2017, Spring 2018
Machine Learning
- Computational and Applied Mathematics, Sungkyunkwan University, Fall 2024–2025
- Scientific Computing and Deep Learning, Fall 2026
- Probabilistic Generative Models (graduate), Sungkyunkwan University, Fall 2024
- Machine Learning (graduate), Chonnam National University (CNU), Spring 2022
- Deep Learning (graduate), Chonnam National University (CNU), Fall 2020–2022
- Advanced Deep Learning (graduate), Chonnam National University (CNU), Fall 2023
- Machine Learning, Chonnam National University (CNU), Spring 2023
- Deep Learning, Chonnam National University (CNU), Fall 2021–2023
- Advanced Machine Learning, Chonnam National University (CNU), Spring 2023
- Advanced Deep Learning, Chonnam National University (CNU), Fall 2023
Mathematics
- Calculus 1, Spring 2026
Programming & Computing
- Data Science Computing (graduate), Chonnam National University (CNU), Spring 2021
- Linux Systems, Chonnam National University (CNU), Fall 2021–2022
Students who wish to study financial mathematics in our group should master the core topics below, which are covered systematically in the following courses.
- Basic Financial Mathematics (기초금융수학) — fundamentals of financial markets: stocks, bonds, futures, and options.
* May be substituted by related courses such as “Investments” or “Derivatives” offered by the Business school. - Computational and Applied Mathematics (전산응용수학) or Scientific Computing and Deep Learning (과학계산과 딥러닝) — foundations of machine learning and deep learning.
* May be substituted by machine-learning courses offered by Statistics, Computer Science, or Electrical & Electronic Engineering. - Financial Mathematics (금융수학) — fundamentals of derivatives, stochastic calculus, and Black–Scholes theory.
- Advanced Financial Mathematics (고급금융수학) — stochastic-control-based deep-learning methods such as the Merton investment–consumption model, PG-DPO, and Deep BSDE.