Will Schwarzer

Autonomous Learning Laboratory, UMass Amherst.

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Hey there, I’m Will. I’m a PhD student at the University of Massachusetts Amherst, where I work with Philip Thomas, Bruno Castro da Silva and Scott Niekum. I work on AI alignment, evaluation, and oversight, and broadly associate with both the RL and safety communities. My long-term goal is to safely realize the benefits of abundant intelligence.

Fun fact: this headshot was taken at an excellent studio in Beijing while I was studying Mandarin there. I’m always happy to chat in Chinese. Aside from languages, I also enjoy playing the piano and rock climbing. I particularly love exploring climbing gyms in new countries (tally so far: three in Beijing, one in Bangkok, one in Istanbul, one in Fort William, Scotland, one in London, and a few in Montreal).

Note to prospective undergraduate and master’s collaborators: please read this before reaching out.

Note on LLM use: In general and where not prohibited, text under my name may have been drafted and edited using the assistance of LLMs. I take responsibility for and believe the correctness of all text under my name (the ICMJE authorship guidelines are a good example of what I take this to entail).

news

Jan 30, 2026 I’m thrilled to announce that our paper Are Deep Speech Denoising Models Robust to Adversarial Noise? has been accepted at ICLR 2026!
Sep 23, 2025 I’m proud to announce that our preprint Evaluation-Aware Reinforcement Learning has been published on arXiv!
Sep 19, 2025 I’m pleased to have served as a reviewer for the Reliable ML from Unreliable Data workshop at NeurIPS 2025.
Sep 08, 2025 I’ve joined Amazon as an Applied Scientist Intern, working on agentic evaluation frameworks for language model agents.
May 09, 2025 I’m pleased to announce that our paper Reinforcement Learning from Human Feedback with High-Confidence Safety Guarantees has been accepted for publication at RLC 2025!
Apr 04, 2025 I’m pleased to have served as a Senior Reviewer for RLC 2025! (Last year, I served as a Technical Reviewer for RLC 2024.)
Mar 16, 2025 I’m proud to announce that our preprint Are Deep Speech Denoising Models Robust to Adversarial Noise? has been published on arXiv!
Feb 25, 2025 I’m proud to announce that our preprint Supervised Reward Inference has been published on arXiv!