Hi, I am Yulu Gan, a second-year CS PhD at MIT, studying AI and Science. Advised by Tomaso Poggio and Phillip Isola. My research draws inspiration from biological evolution to design algorithms and enable algorithm-hardware co-design, with a focus on understanding and improving LLMs and VLMs. I have interned at Microsoft Research, Cognizant and will be interning at NVIDIA in Santa Clara this summer.
Recent Publications* indicates equal contribution.
All publications →Neural Thickets: Diverse Task Experts Are Dense Around Pretrained WeightsICML 2026 Spotlight
A Game of Random Guessing
Blog
Open notebook
Pretrained LLMs Are Surrounded by Task Experts
Evolution Strategies at Scale: LLM Fine-Tuning Beyond Reinforcement LearningICML 2026
A new way to fine-tune LLMs just dropped
48,640 views
2,620 likes
178 comments
How to Finetune 8 Billion Parameters with Evolution Strategies?
3,248 views
151 likes
12 comments
exploring "Evolution Strategies at Scale for LLM Finetuning" | Deep Learning Study Session
1,168 views
45 likes
11 comments
Selected Awards
McGovern Institute Student Fellow
Dr. Chiang Chen Fellowship
Frederick R. (1953) and Barbara Cronin Fellowship
AAAI Best Student Paper Award (project lead)
Second Place in RoboCup China Open (team lead)
First Place in China Mathematical Olympiad, Zhejiang Division
Blog
See all →
To be updated.