About
I am an Assistant Professor in the Department of Mathematics at Sookmyung Women's University (since March 2026). My research sits at the intersection of pure mathematics and applied AI, organized along three axes. On the mathematical side, I work on homogeneous dynamics, Diophantine approximation, and topological data analysis (TDA). On the methodological side, I develop graph neural networks / graph transformers and generative models on manifolds (flow matching, diffusion). I bring these tools to applications in electronic design automation (EDA) and semiconductor AI, simulation-driven molecular generation, and medical data science. Prior to joining Sookmyung, I was a Staff Engineer at Samsung Electronics AI Center.
한국어 소개 보기
저는 숙명여자대학교 수학과 조교수입니다 (2026년 3월 임용). 순수수학과 응용 AI의 경계에서 연구하며, 세 축으로 구성됩니다. 수학적 기반 으로는 homogeneous dynamics, Diophantine approximation, 그리고 topological data analysis (TDA) 를 다루고, 방법론 으로는 graph neural networks / graph transformers 와 manifold 위의 generative models (flow matching, diffusion) 를 개발합니다. 이 도구들을 응용 측에서 electronic design automation (EDA)·반도체 AI, 시뮬레이션 기반 분자 생성, medical data science 에 연결하고 있습니다. 숙명여대 부임 이전에는 삼성전자 AI Center 에서 반도체 설계·검증을 위한 AI 를 연구하는 Staff Engineer 로 재직했습니다.
News
- 2026-06-25 talk Talk at the 3rd Korea EDA Workshop (SNU): The Spectrum of a Circuit — Rethinking EDA through the Graph Laplacian
- 2026-05-13 talk Invited seminar at Chung-Ang University, Dept. of Mathematics
- 2026-05-04 talk Invited seminar at Pusan National University — Geometry & Topology Seminar
- 2026-04-13 talk Colloquium at Sookmyung Women's University, Dept. of Statistics
- 2026-03-01 appointment Joined Sookmyung Women's University as Assistant Professor of Mathematics
- 2026-02-01 paper BADGE accepted at DATE 2026 (Verona, Italy)
Research Interests
Mathematical Foundations
- Homogeneous Dynamics
- Diophantine Approximation
- Topological Data Analysis
Geometric & Graph-based Learning
- Graph Neural Networks & Graph Transformers
- Generative Models on Manifolds
- LLM Agents on Graph Tasks
Applications
- Electronic Design Automation (EDA)
- AI for Molecular Generation
- Medical Data Science