University of Waterloo
James BradburyHead of Compute · AnthropicResearcher↗
Researcher · Engineer
Tristan Hume
AnthropicMember of Technical Staff
Hume leads performance optimization at Anthropic, making large AI systems run more efficiently. Earlier there he worked on mechanistic interpretability—tools for understanding model internals—and at Jane Street he created the magic-trace performance-analysis tool.
Career & education
Current roleAnthropicFeb 2022-presentMember of Technical Staff
AnthropicFeb 2022-presentPreviously
Jane Street2019-2021Developer
Jane Street2019-2021Education
Work and education history is primarily focused on AI-relevant roles and may not be comprehensive.
Citation Trend
Total citations to scholarly work, including research papers, technical reports, books and theses, as recorded by Google Scholar. Each point is a dated snapshot.
citations24,046As of Nov 3, '26
citations+6,506Since last snapshot, Jun 15, '26
Selected contributions
Constitutional AI: Harmlessness from AI Feedback
With Yuntao Bai, Saurav Kadavath, Sandipan Kundu, Amanda Askell, Jackson Kernion, Andy Jones, Anna Chen and others ·Trained AI assistants to critique and improve their answers using a written set of principles.
Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback
With Yuntao Bai, Andy L. Jones, Kamal Ndousse, Amanda Askell, Anna Chen, Nova DasSarma, Dawn Drain and others ·Training AI assistants to be more helpful and less harmful using human feedback.
Based on public sources. If accuracy is important, verify details using the links or references.
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Reviewed August 9, 2026 · Checked for accuracy and new information.
