About
My research goal is to develop AI tools for materials and drug discovery. I have conducted research on generative models and evaluation tools for scientific discovery, and I am currently building these into a unified platform.
Going forward, I plan to advance this platform with Agent AI and integrate it with Auto Lab to enable fully automated scientific workflows.
Research Interests
AI for Scientific Discovery
Developing AI tools for materials and drug discovery, including molecular dynamics simulation, molecular generation, and crystal generation.
Generative Models
Building generative models such as generative flow networks, diffusion models, and flow models for sampling complex distributions in scientific domains.
Agent AI Systems
Building a materials generation platform and integrating it as the generation module of Auto Lab, with LLM-based control to advance the software component of Auto Lab toward fully automated scientific workflows.
Publications
Multimodal Crystal Flow: Any-to-Any Modality Generation for Unified Crystal Modeling
Kiyoung Seong, Sungsoo Ahn, Sehui Han, Changyoung Park
Preprint 2026
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
On Scalable and Efficient Training of Diffusion Samplers
Minkyu Kim*, Kiyoung Seong*, Dongyeop Woo, Sungsoo Ahn, Minsu Kim(* equal contribution)
NeurIPS 2025
Learning Collective Variables from BioEmu with Time-Lagged Generation
Seonghyun Park, Kiyoung Seong, Soojung Yang, Rafael Gómez-Bombarelli, Sungsoo Ahn
ICLR 2026
Energy-Based Generator Matching: A Neural Sampler for General State Space
Dongyeop Woo, Minsu Kim, Minkyu Kim, Kiyoung Seong, Sungsoo Ahn
NeurIPS 2025
Experience
- 2025.03 — Present
- 2025.09 — 2026.02
- 2023.06 — 2025.02
Researcher
POSTECH, CSE
- 2017.03 — 2023.02
B.S. in Mathematics Education (Advanced Mathematics Track)
Korea University