I am an MS student at Systems Intelligence Lab in KAIST, advised by Prof. Jinkyoo Park. My research focuses on probabilistic machine learning, generative models, structure learning, deep-learning-based reasoning, neurosymbolic methods, system 2 AI, and AI Safety. Recently, I’m particularly interested in generative flow networks (GFlowNets) and their applications. Here is my CV (last updated on Feb 2025).
📝 Publications
* indicates equal contribution.
- Neural Genetic Search in Discrete Spaces [paper] [code]
Hyeonah Kim*, Sanghyeok Choi*, Jiwoo Son, Jinkyoo Park, Changhyun Kwon
arXiv 2025 - Adaptive teachers for amortized samplers [paper]
Minsu Kim*, Sanghyeok Choi*, Taeyoung Yun, Emmanuel Bengio, Leo Feng, Jarrid Rector-Brooks, Sungsoo Ahn, Jinkyoo Park, Nikolay Malkin, Yoshua Bengio
ICLR 2025 - Improved Off-policy Reinforcement Learning in Biological Sequence Design [paper]
Hyeonah Kim, Minsu Kim, Taeyoung Yun, Sanghyeok Choi, Emmanuel Bengio, Alex Hernández-García, Jinkyoo Park
arXiv 2024 & NeurIPS 2024 Workshop on AI for New Drug Modalities - Ant Colony Sampling with GFlowNets for Combinatorial Optimization [paper], [code]
Minsu Kim*, Sanghyeok Choi*, Hyeonah Kim, Jiwoo Son, Jinkyoo Park, Yoshua Bengio
AISTATS 2025 - Genetic-guided GFlowNets: Advancing in Practical Molecular Optimization Benchmark [paper], [code]
Hyeonah Kim, Minsu Kim, Sanghyeok Choi, Jinkyoo Park
NeurIPS 2024 - Equity-Transformer: Solving NP-Hard Min-Max Routing Problems as Sequential Generation with Equity Context [paper], [code]
Jiwoo Son*, Minsu Kim*, Sanghyeok Choi, Hyeonah Kim, Jinkyoo Park
AAAI 2024 - Rl4co: an extensive reinforcement learning for combinatorial optimization benchmark [paper], [code]
Federico Berto*, Chuanbo Hua*, Junyoung Park*, Laurin Luttmann, Yining Ma, Fanchen Bu, Jiarui Wang, Haoran Ye, Minsu Kim, Sanghyeok Choi, Nayeli Gast Zepeda, André Hottung, Jianan Zhou, Jieyi Bi, Yu Hu, Fei Liu, Hyeonah Kim, Jiwoo Son, Haeyeon Kim, Davide Angioni, Wouter Kool, Zhiguang Cao, Qingfu Zhang, Joungho Kim, Jie Zhang, Kijung Shin, Cathy Wu, Sungsoo Ahn, Guojie Song, Changhyun Kwon, Kevin Tierney, Lin Xie, Jinkyoo Park
arXiv 2023 - Multi-agent reinforcement learning based actuator control for EV HVAC systems [paper]
Sungho Joo, Dongmin Lee, Minseop Kim, Taeho Lee, Sanghyeok Choi, Seungju Kim, Jeyeol Lee, Joongjae Kim, Yongsub Lim, Jeonghoon Lee
IEEE Access 2022
📖 Education
- Sep 2023 - Aug 2025 (Expected), MS in Industrial & Systems Engineering, KAIST.
- Mar 2017 - Aug 2023, BBA and BS in Industrial Engineering, Seoul National University.
💻 Experience
- Sep 2022 - Aug 2023, Undergraduate Resercher @ Systems Intelligence Lab, KAIST.
- Jan 2022 - Aug 2022, Machine Learning Research Engineer (Intern) @ MakinaRocks.
- Mar 2021 - Dec 2021, Undergraduate Researcher @ Vision & Learning Lab, Seoul National University.
- Mar 2019 - Jan 2021, Military Service @ R.O.K Airforce.
⭐ Open Source Projects
🎖 Honors and Awards
- Jul 2020, 1st place in Manufacturing Process Optimization with AI (Competition), DACON & LG Science Park.
- May 2020, 1st place in Nowcast Prediction (Competition), DACON & KIMM.
- Oct 2017, Bang Il-Young Scholarship (Full-tuition and living stipend for 3 years), The Bang Il-Young Foundation.