Ph.D. Candidate in Industrial and Systems Engineering at KAIST

I am a member of the Systems Intelligence Lab (advised by Prof. Jinkyoo Park) and Computational Optimization Methods Lab (co-advised by Prof. Changhyun Kwon). My research focuses on machine learning for practical combinatorial optimization, e.g., large-scale vehicle routing problems, hardware design optimization, and molecular optimization. Here is my cv.

🔥 News

• Jan 2025:  🎉🎉 One paper accepted to AISTATS 2025
• Dec 2024:  🎉🎉 Google Conference Scholarship for NeurIPS 2024
• Dec 2024:  🎉🎉 “Genetic-guided GFlowNets for Sample Efficient Molecular Optimization” is selected for a contributed talk at the WiML workshop (NeurIPS 2024)
• Oct 2024:  🎉🎉 One paper accepted to NeurIPS 2024
• Sep 2024:  🎉🎉 “A Neural Separation Algorithm for the Rounded Capacity Inequalities” is selected as a featured article (INFORMS Journal on Computing)
• May 2024:  🎉🎉 One paper accepted to ICML 2024

📝 Publications

([C]: Conference, [J]: Journal, [W]: Workshop, [P]: Preprint)

• [P] Neural Genetic Search in Discrete Spaces [paper], [code]
  Hyeonah Kim*, Sanghyeok Choi*, Jiwoo Son, Jinkyoo Park, Changhyun Kwon\

• [C] Ant Colony Sampling with GFlowNets for Combinatorial Optimization [paper], [code]
  Minsu Kim*, Sanghyeok Choi*, Hyeonah Kim, Jiwoo Son, Jinkyoo Park, Yoshua Bengio
  AISTATS 2025

• [W] Improved Off-policy Reinforcement Learning in Biological Sequence Design [paper], [code]
  Hyeonah Kim, Minsu Kim, Taeyoung Yun, Sanghyeok Choi, Emmanuel Bengio, Alex Hernández-García, Jinkyoo Park AIDrugX@NeurIPS

• [C] Genetic-guided GFlowNets for Sample Efficient Molecular Optimization [paper], [code]
  Hyeonah Kim, Minsu Kim, Sanghyeok Choi, Jinkyoo Park
  NeurIPS 2024

• [C] Symmetric Replay Training: Enhancing Sample Efficiency in Deep Reinforcement Learning for Combinatorial Optimization [paper], [code]
  Hyeonah Kim, Minsu Kim, Sungsoo Ahn, Jinkyoo Park
  ICML 2024

• [C] 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

• [J, W] A Neural Separation Algorithm for the Rounded Capacity Inequalities [paper], [code]
  Hyeonah Kim, Jinkyoo Park, Changhyun Kwon
  INFORMS Journal on Computing (IJOC), 2024
  NeurIPS 2022 GLFrontiers Workshop

• [W] RL4CO: a Unified Reinforcement Learning for Combinatorial Optimization Library [paper], [code]
  Federico Berto*, Chuanbo Hua*, Junyoung Park*, Minsu Kim, Hyeonah Kim, Jiwoo Son, Haeyeon Kim, Joungho Kim, Jinkyoo Park
  NeurIPS 2023 Workshop: New Frontiers in Graph Learning (Oral)

• [C] Meta-SAGE: Scale Meta-Learning Scheduled Adaptation with Guided Exploration for Mitigating Scale Shift on Combinatorial Optimization [paper], [code]
  Jiwoo Son*, Minsu Kim*, Hyeonah Kim, Jinkyoo Park
  ICML 2023

🎖 Honors and Awards

• Dec 2024: Google Conference Scholarship for NeurIPS 2024 (1st author of Genetic-guided GFlowNets for Sample Efficient Molecular Optimization)
• Nov 2024: KAIST 2024 best paper (1st author of A Neural Separation Algorithm for the Rounded Capacity Inequalities)

📖 Educations

• Mar 2021 - Feb 2025, Ph.D. Candidate in Industrial and Systems Engineering, KAIST (SILAB & COMET Lab)
• Mar 2019 - Feb 2021, M.S in Industrial Engineering, Seoul National University (Optimization and Operational Research Lab)
• Mar 2011 - Feb 2015, B.S Industrial Engineering, Hanyang University (Information Design Lab)

💻 Work Experience

• Jan 2015 - Jun 2017, Software Engineer at LGE ERP Manufacturing, LGCNS