Jaewon Kim

Welcome! I am an undergraduate student in Semiconductor Engineering at Korea University and an undergraduate researcher at the Complex Data Analytics Lab (CDAL), advised by Prof. Junhee Seok.

My research interests center on advancing machine learning methods that are built on strong mathematical foundations while remaining applicable to real-world problems. I am particularly interested in how concepts from probability, differential equations, and physics can guide the design of more reliable and efficient learning algorithms, with applications ranging from generative models to reinforcement learning. In particular, I study areas such as generative models, stochastic partial differential equations, deep reinforcement learning, and physics-informed machine learning.

I believe that blending these directions provides a pathway toward models that are not only powerful but also grounded in mathematical principles.

You can find more details about my academic background and experiences in my Curriculum Vitae (CV).

Research Interests

• Generative Models
• Stochastic Partial Differential Equations
• Deep Reinforcement Learning
• Physics-Informed Machine Learning