Michael Chen
Research papers (technical governance or ML) related to evaluating and mitigating dangerous AI capabilities, with a focus on what's actionable and relevant for AGI companies
Stream overview
Broad topics I am interested in include:
- Frontier safety policies and proposing actionable improvements for companies
- Existing frontier safety regulation, such as EU GPAI Code of Practice or SB 53
- Dangerous capability evaluations and mitigations, especially related to loss of control
- Making frontier safety practices more likely to be adopted in China, e.g., by analyzing relevant EU/California regulation
Mentors
Michael Chen works on AI policy at METR and is a part-time PhD student at Oxford in technical AI governance. Michael previously worked as a software engineer at Stripe. METR's policy team has assisted companies like Google DeepMind, Amazon, and Anthropic with developing their frontier safety policies – voluntary commitments to evaluate and mitigate severe AI risks. Besides corporate advising, Michael has provided feedback on U.S. state bills and the EU AI Act GPAI Code of Practice.
Mentorship style
I like to get daily standup messages about progress that has been made on the project, and I'm happy to provide some quick async feedback on new outputs. I'll also have weekly meetings. I'm based in Constellation in Berkeley.
Fellows we are looking for
Good writers/researchers who can work independently and autonomously! I'm looking for scholars who can ship a meaningful research output end-to-end and ideally have prior experience in writing relevant papers.
Project selection
I may assign a project, have you pick from a list of projects, or talk through project ideas with you.
The Winter 2026 cohort offers a wide range of research streams led by experts across AI alignment, interpretability, governance, and safety. Each stream provides its own research agenda, methodology, and mentorship focus.
