Vint Lee

Hello! I'm a researcher at Amazon AGI SF, where I currently work on reinforcement learning for web-browsing agents.

I completed my MS in EECS and BA in CS and Math at UC Berkeley, where I had the pleasure of working on Machine Learning research under the mentorship of Pieter Abbeel, Youngwoon Lee, and John Wawrzynek.

Email  /  Twitter  /  Github

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Research

I'm interested in deep learning in general, and RL for LLMs in particular. In the past, I've also worked on model-based RL and diffusion models.

Chip Placement with Diffusion Models
Vint Lee, Minh Nguyen, Leena Elzeiny, Chun Deng, Pieter Abbeel, John Wawrzynek
ICML, 2025
code / arXiv

We train diffusion models to perform macro placement, an important step in designing chips, using our novel data-generation algorithm and model architecture.

DreamSmooth: Improving Model-based Reinforcement Learning via Reward Smoothing
Vint Lee, Pieter Abbeel, Youngwoon Lee
ICLR, 2024
project page / code / arXiv

Reward smoothing provides significant improvement to performance of model-based RL algorithms in many sparse-reward environments.

Low-cost, Lightweight Electronic Flow Regulators for Throttling Liquid Rocket Engines
Vint Lee, Sohom Roy
IAC, 2023. Best Undergraduate Paper Award
project page / code / arXiv

Electronic pressure regulators enable more flexible and accurate control of pressures in liquid rocket engines, opening up new capabilities for collegiate teams such as throttling.


Website template from Jon Barron.