I’m a second-year PhD student at KAIST AI, advised by Sungsoo Ahn. I work on generative modeling and probabilistic inference for AI for Science, with a focus on:

1. Sampling: Boltzmann generators, molecular conformation generation, and efficient sampling on manifolds.
2. Scientific design: Small-molecule, protein structure, DNA sequence, and materials generation.

News

• May 2025 Two papers accepted at NeurIPS 2025.
• Mar 2025 Started my PhD at KAIST AI, Structured and Probabilistic Machine Learning Lab.
• Aug 2024 New preprint on arXiv.
• Oct 2023 One paper accepted at TMLR 2024.

Publications

Energy-based generator matching: A neural sampler for general state space

Dongyeop Woo, Minsu Kim, Minkyu Kim, Kiyoung Seong and Sungsoo Ahn

NeurIPS 2025

On scalable and efficient training of diffusion samplers

Minkyu Kim, Kiyoung Seong, Dongyeop Woo, Sungsoo Ahn, Minsu Kim

NeurIPS 2025

Iterated energy-based flow matching for sampling from boltzmann densities

Dongyeop Woo and Sungsoo Ahn

Arxiv preprint

Non-backtracking graph neural networks

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

TMLR 2024

Curriculum Vitae