Seonghyun Park

Bio

Hello! I'm a Ph.D. student at Kim Jaechul Graduate School of AI at KAIST, advised by Sungsoo Ahn. My research interests are mainly on AI4Science, specifically integrating machine learning to advance scientific discovery on small molecules and proteins! I'm interested in the following topics:

Small molecule (drug) property predictions, LLM Agents
Molecular Dynamics (MD) simulation
Machine Learning Collective Variables
Graph neural networks (GNNs), Over-squashing

Publications

Most recent publications on Google Scholar.
^† indicates equal contribution, ^‡ indicates co corresponding author.

Selected
All

Learning Collective Variables for Enhanced Sampling from BioEmu with Time-lagged Generation

Seonghyun Park, Kiyoung Seong, Soojung Yang, Rafael Gómez-Bombarelli, Sungsoo Ahn

ICLR 2026
ICML 2025, Workshop GenBio

Paper

Transition path sampling with improved off-policy training of diffusion path samplers

Kiyoung Seong, Seonghyun Park, Seonghwan Kim, Woo Youn Kim, Sungsoo Ahn

ICLR 2025
ICML 2024, Workshop SPIGM

Paper Page

Non-backtracking Graph Neural Networks

Seonghyun Park^†, Narae Ryu^†, Gahee Kim, Dongyeop Woo, Se-Young Yun^‡, Sungsoo Ahn^‡

TMLR 2024
NeurIPS 2023, Workshop on New Frontiers in Graph Learning (GLFrontiers) (Oral)

Paper

Learning Collective Variables for Enhanced Sampling from BioEmu with Time-lagged Generation

Seonghyun Park, Kiyoung Seong, Soojung Yang, Rafael Gómez-Bombarelli, Sungsoo Ahn

ICLR 2026
ICML 2025, Workshop GenBio

Paper

Transition path sampling with improved off-policy training of diffusion path samplers

Kiyoung Seong, Seonghyun Park, Seonghwan Kim, Woo Youn Kim, Sungsoo Ahn

ICLR 2025
ICML 2024, Workshop SPIGM

Paper Page

Non-backtracking Graph Neural Networks

Seonghyun Park^†, Narae Ryu^†, Gahee Kim, Dongyeop Woo, Se-Young Yun^‡, Sungsoo Ahn^‡

TMLR 2024
NeurIPS 2023, Workshop on New Frontiers in Graph Learning (GLFrontiers) (Oral)

Paper

Diffusion Probabilistic Models for Structured Node Classification

Hyosoon Jang, Seonghyun Park, Sangwoo Mo, Sungsoo Ahn

NeurIPS 2023
ICML 2023, Workshop on Structured Probabilistic Inference & Generative Modeling

Paper

Vitæ

Full Resume in PDF.

KAIST AI 2025 -

Ph.D. Student
Structured and Probabilistic Machine Learning (SPML) Lab
POSTECH 2023 - 2025

Master's Degree
Machine Learning (ML) Lab
INSA Lyon Spring 2022

Exchange student
Bioinformatique
Bagelcode Summer 2021

Buisness Analyst, Intern
BA Team
Sellerhub Summer 2020

Product Manager, Intern
PM Team
POSTECH 2019 - 2022

Bachelor's Degree
Computer Science and Engineering

Website Design

Thanks Martin Saveski for this awesome webiste template!