Hi! I’m Andy, an undergraduate Researcher and Engineer at UC Berkeley studying Electrical Engineering and Computer Science (EECS).

My research interests lie in building efficient and generalizable AI using Reinforcement Learning and interacting with the world through Robotics. Currently, I’m working on offline-to-online RL at Berkeley Artifical Intelligence Research, advised by professor Sergey Levine. Outside my research, I enjoy building applied machine learning applications with my friends at Launchpad. I’ll also be working on LLM training and infrastructure at NVIDIA this summer.

If you’d like to chat, please reach out at [andypeng at berkeley dot edu].

Recent News

last updated: Dec 2024

• I just released my first ever research paper with BAIR! We explore how to do RL fine-tuning without offline data retention. I’m excited to see how Warm-start RL (WSRL) can help scale up RL for real-world tasks, and the future of efficient RL finetuning. (Update: WSRL has been accepted to ICLR 2025!)