collaboration

I have been fortunate to work with many talented junior collaborators and mentees, and I have learned a great deal from them!

Current Collaborators

• Yuyuan Chen (Harvard): Reinforcement learning for generative models.
• Minji Lee (Columbia University): Generative models for protein design.
• Sunwoo Kim (MIT).
• Jiwhan Kim (Seoul National University).
• Woobin Park (Seoul National University): Diffusion model training.
• David Ko (MIT).
• Kwonhee Moon (Seoul National University).
• Yunghee Lee (KAIST).

Past Collaborators

• Kiwhan Song (OpenAI): 2025, diffusion models.
• Junsu Kim (Student Researcher at Google Deepmind): 2025, convergence analysis for LoRA.
• Brian Lee (Jane Street): 2025, flexible-length discrete diffusions.
• Seunggeun Kim and Taekyun Lee (UT Austin): 2025–2026, inference-time algorithms for discrete diffusions.
• Jonathan Geuter (Harvard): 2026, discrete diffusion model training.
• Woosang Jeon (Seoul National University): 2026, reinforcement learning for generative models.
• Pranav Sitaraman (Tesla) and Gavin Ye (Google DeepMind): 2026, diffusion model inference.

These collaborations have taken the form of either close research partnerships or mentoring relationships. In all cases, I aim to stay deeply involved in each project, at a co-first-author level of contribution!

Due to limited capacity, I do not have dedicated mentoring spots available for the Fall 2026 semester, but I expect to have one or two openings beginning in Spring 2027. If you are interested in generative modeling for scientific domains or in developing a deep understanding of generative modeling, please feel free to email me at jaeyeon_kim@g.harvard.edu.