About Me
I’m a 3rd-year Ph.D. student in the Machine Learning and Artificial Intelligence (MLAI) lab at KAIST, under the supervision of Prof. Sung Ju Hwang. I’m also working as a research intern in the NVIDIA Fundamental Generative AI Research (GenAIR) team. I am fortunate to be a recipient of the NVIDIA Graduate Fellowship. My research interests include AI for science and generative models.
☕️ My email/DM are always open to anyone interested in discussion/collaboration!
Education
- Ph.D. student, Graduate School of AI
KAIST, Sep. 2022 - present. - M.S., Graduate School of AI
KAIST, Mar. 2021 - Aug. 2022. - B.S., Aerospace Engineering / Biological Sciences (Double Major)
KAIST, Mar. 2015 - Aug. 2019.
Research Experience
- Research Intern, NVIDIA
Feb. 2024 - Sep. 2025, Santa Clara, CA, US
Research topic: Generative AI for science
Mentors: Weili Nie, Karsten Kreis, and Arash Vahdat - Research Intern, AITRICS
Jan. 2021 - Feb. 2021, South Korea
Research topic: Docking-optimized molecule generation using RL
Publications
*: equal contribution
- Rethinking Molecule Synthesizability with Chain-of-Reaction
Seul Lee, Karsten Kreis, Srimukh Prasad Veccham, Meng Liu, Danny Reidenbach,
Saee Paliwal, Weili Nie, and Arash Vahdat
Under Review, 2025. - GenMol: A Drug Discovery Generalist with Discrete Diffusion
Seul Lee, Karsten Kreis, Srimukh Prasad Veccham, Meng Liu, Danny Reidenbach,
Yuxing Peng, Saee Paliwal, Weili Nie†, and Arash Vahdat† (†: equal advising)
ICML, 2025. [paper] - Molecule Generation with Fragment Retrieval Augmentation
Seul Lee, Karsten Kreis, Srimukh Prasad Veccham, Meng Liu, Danny Reidenbach,
Saee Paliwal, Arash Vahdat†, and Weili Nie† (†: equal advising)
NeurIPS, 2024. [paper][code][project page] - READRetro: Natural Product Biosynthesis Planning with
Retrieval-Augmented Dual-View Retrosynthesis
Seul Lee*, Taein Kim*, Min-Soo Choi, Yejin Kwak, Jeongbin Park, Sung Ju Hwang, and Sang-Gyu Kim
New Phytologist, 2024 (IF=8.3). [paper][code][web] - Drug Discovery with Dynamic Goal-aware Fragments
Seul Lee, Seanie Lee, Kenji Kawaguchi, and Sung Ju Hwang
ICML, 2024. [paper][code]
ICLR Machine Learning for Genomics Explorations Workshop (Spotlight), 2024. - Protein Representation Learning by Capturing Protein Sequence-Structure-Function Relationship
Eunji Ko*, Seul Lee*, Minseon Kim*, Dongki Kim, and Sung Ju Hwang
ICLR Machine Learning for Genomics Explorations Workshop (Spotlight), 2024. [paper] - A Simple and Scalable Representation for Graph Generation
Yunhui Jang, Seul Lee, and Sungsoo Ahn
ICLR, 2024. [paper]
NeurIPS New Frontiers in Graph Learning Workshop, 2023. - Exploring Chemical Space with Score-based Out-of-distribution Generation
Seul Lee, Jaehyeong Jo, and Sung Ju Hwang
ICML, 2023. [paper][code]
ICLR Machine Learning for Drug Discovery Workshop (Oral), 2023. - Score-based Generative Modeling of Graphs via the System of Stochastic Differential Equations
Jaehyeong Jo*, Seul Lee*, and Sung Ju Hwang
ICML, 2022. [paper][code] - Edge Representation Learning with Hypergraphs
Jaehyeong Jo*, Jinheon Baek*, Seul Lee*, Dongki Kim, Minki Kang, and Sung Ju Hwang
NeurIPS, 2021. [paper][code] - Hit and Lead Discovery with Explorative RL and Fragment-based Molecule Generation
Soojung Yang, Doyeong Hwang, Seul Lee, Seongok Ryu, and Sung Ju Hwang
NeurIPS, 2021. [paper][code] - Robotic Scanning Technology for Laser Pulse-Echo Inspection
Seul Lee, Jong-min Hyun, Hasan Ahmed, and Jung-ryul Lee
Electronics Letters, 2020. [paper]
Awards and Honors
- NVIDIA Graduate Fellowship, 2025-2026.
- KAIST Summa Cum Laude, Aug. 2019.
- KAIST Dean’s List (College of Engineering), Aug. 2018.
- KAIST Dean’s List (College of Engineering), Feb. 2018.
- Boeing Undergraduate Scholarship, 2018-2019.
- KAIST Presidential Fellowship (KPF), 2017-2019.
- KAIST Dean’s List (College of Life Science & Bioengineering), Feb. 2017.
- National Science and Engineering Undergraduate Scholarship, 2015-2019.