About
I'm an M.S. candidate in Computer Science at Yonsei University, working on AI-driven drug discovery under the supervision of Prof. Sanghyun Park.
My research focuses on building and validating robust AI models for protein–ligand interaction analysis and generative molecule design. Specifically, I develop diffusion-based frameworks for structure-based drug design (SBDD) that generate selective 3D molecular structures, as well as physics-informed scoring functions for interpretable binding affinity prediction.
With a dual undergraduate background in Computer Engineering and Healthcare Convergence, I aim to bridge the gap between deep learning theory and real-world drug discovery challenges.
Structure-Based Drug Design
Protein-Ligand Interaction
Diffusion Models
3D Molecular Generation
Binding Affinity Prediction
Selective Drug Design
Equivariant GNNs
Education
Current
2025.03 —
2025.03 —
M.S. in Computer Science
연세대학교 신촌캠퍼스 (Yonsei University)
Advisor: Prof. Sanghyun Park · AI-driven Drug Discovery
Graduated
2019.03 — 2025.02
2019.03 — 2025.02
B.E. in Computer Engineering
연세대학교 미래캠퍼스 (Yonsei University, Mirae Campus)
Double Major: Healthcare Convergence
Total GPA: 4.08/4.5 · Major GPA: 4.09/4.5
Total GPA: 4.08/4.5 · Major GPA: 4.09/4.5
Publications
PAKDD 2026
1st Author
Regular Paper
TheSelective: Dual Affinity-Guided Diffusion Model for Selective Molecular Generation
Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2026
KCC 2025
1st Author
Extended Diffusion Model for Molecular Graph Generation Incorporating Distance Matrix
Korea Computer Congress (KCC), Jeju, Korea, 2025
KCC 2024
Comparison of Inference Acceleration Performance of CPU-based Image Classification Models
Korea Computer Congress (KCC), Jeju, Korea, 2024
Experience
Current
2025.03 —
2025.03 —
Graduate Researcher
Yonsei University, Sinchon Campus
AI 기반 Structure-Based Drug Design 연구. Diffusion 모델을 활용한 선택적 분자 생성 및 Protein-Ligand Interaction 기반 결합 친화도 예측 프레임워크 개발.
2024.06 — 2024.07
Short-Term International Research Intern
University of Nevada, Las Vegas (UNLV), USA
Machine learning 강의 수강 및 위성 이미지 기반 Image Segmentation 프로젝트 수행.
2024.03 — 2024.06
Undergraduate Research Assistant
Applied Data Science LAB, Yonsei Univ. Mirae Campus
랩 세미나 논문 리뷰 발표 및 Drug Repositioning 연구 보조.
Projects
2025 — Present
TheSelective: Selective Molecular Generation
이중 결합 친화도 예측기를 활용한 Diffusion 기반 선택적 분자 생성. On-target 결합 강화 + Off-target 억제 guidance 전략.
Diffusion
SBDD
Selectivity
PyTorch
2025.05 — 2025.11
LAIDD Mentoring Project: Small Molecule Generation & Target Activity Prediction
저분자 화합물 생성 및 표적 단백질에 대한 활성 예측. 한국제약바이오협회(KPBMA) 주관 AI 신약개발 멘토링 프로젝트.
LAIDD
Mol Gen
Activity Prediction
KPBMA
2024 — 2025
3D Molecular Graph Generation with Distance Matrix
SDE 기반 Diffusion으로 원자 종류·결합·3D 거리 행렬 동시 생성. 가우시안 커널 거리 통합.
SDE
GNN
QM9
ZINC250k
2024.03 — 2024.06
Drug Repositioning with GCNs
약물-질병 이종 네트워크 기반 GCN link prediction으로 약물 재창출 후보 탐색.
GCN
Heterogeneous Net
10-Fold CV
Awards & Scholarships
2024
2nd Prize, AI-based Medical Data Analysis Competition
Intel Korea
2024
3rd Prize, Digital Healthcare Startup Idea Awards
Yonsei University
2024
Academic Excellence Scholarship (×3)
Yonsei University
2024
SW Major Excellence Scholarship
Yonsei University
2020
1st Prize, Winter Java Training Camp
Yonsei University
2019
1st Prize, Summer C Language Training Camp
Yonsei University
Skills
Deep Learning
PyTorch
PyG
RDKit
Diffusion
GNN
Transformer
Languages
Python
Java
C
SQL
R
LaTeX
Tools & Infra
Git
Linux
Docker
Wandb
VSCode
MySQL