collaboration

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

• 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.
• Yuyuan Chen (Harvard): 2026, reinforcement learning for generative models.
• Minji Lee (Columbia University): Generative models for protein design.
• Woosang Jeon (SNU): 2026, reinforcement learning for generative models.
• Woobin Park (SNU): 2026 –, diffusion model training.
• Pranav Sitaraman (Tesla) and Gavin Ye (Google DeepMind): 2026, diffusion model inference.
• Sunwoo Kim (MIT): 2026.
• Jungsoo Lee (MIT): 2026.

These collaborations have taken the form of either close research effort or mentoring-oriented. 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 foreseeable future.