Yuchen Zhu
Machine Learning PhD @ Georgia Tech 🍀
140 Skiles
686 Cherry St NW
Atlanta, GA 30332
Hi, I am Yuchen Zhu, a 3rd year Machine Learning PhD at Georgia Tech.
My interests lie in the broad aspects of GenAI. My research currently focuses on diffusion models and (multimodal) diffusion LLMs, and their efficient, effective post-training.
At Georgia Tech, I am fortunate to be advised by Molei Tao and Yongxin Chen, and working with a group of incredible researchers. Prior to that, I graduated with MA in Statistics from Yale University and BS in Honors Mathematics with highest honor from NYU Shanghai. During those time, I had the privilege to work with Zhuoran Yang and Mathieu Laurière on theory/numerics of RL and mean-field system.
During Spring 2026, I am a Research Scientist Intern at
Adobe Research, working on post-training of dLLMs at scale.
You can find more details in my CV here.
Contact: yzhu738 [at] gatech [dot] edu
Updates
[01/2026] I start as a Research Scientist Intern at Adobe Research, working on post-training of diffusion LLMs. |
| [10/2025] DMPO is online! Check out a completely new RL paradigm that uniquely leverages characteristics of diffusion LLMs for effective post-training! Code is available at here. |
| [10/2025] TR2-D2 is online! Discover the SOTA method for finetuning MDM for bio seqs design with tree search + off-policy RL! |
| [09/2025] MDNS and Discrete Fast Solvers got accepted to NeurIPS 2025, see you in San Diego! |
| [05/2025] Learning to Stop and Diffuse Everything got accepted to ICML 2025, see you in Vancouver! |
| [04/2025] I wrote a new blog on how group structures aid generative modeling of manifold data. |
| [01/2025] TDM and STEM got accepted to ICLR 2025, see you in Singapore! |
Talks
| [03/2026] INFORMS Optimization Society Conference 2026 |
| [09/2025] GT ML Student Conference |
| [08/2025] MolSS Reading Group |
| [11/2024] GT ML Student Seminar |
| [10/2024] SIAM MDS 2024 |
| [04/2024] Southeast ACM Student Workshop 2024 |
Selected Publications
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Fast Solvers for Discrete Diffusion Models: Theory and Applications of High-Order AlgorithmsAdvances in Neural Information Processing Systems (NeurIPS), 2025