University of Cambridge
Philip TorrProfessor · University of OxfordResearcher↗
Researcher · Academic
Yarin Gal
University of OxfordAssociate Professor
Gal helped pioneer ways for neural networks to measure their own uncertainty.[1] With Zoubin Ghahramani, he showed that dropout—randomly switching off parts of a network—can estimate how confident a model should be. His methods are used in medicine, robotics and scientific research.
Career & education
Current roleUniversity of Oxford2017-presentAssociate Professor
University of Oxford2017-presentWork 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.
citations80,448As of Oct 25, '26
Selected contributions
How to Catch an AI Liar: Lie Detection in Black-Box LLMs by Asking Unrelated Questions
With Lorenzo Pacchiardi, Alex Chan, Sören Mindermann, Ilan Moscovitz, Alexa Pan, Owain Evans and Jan BraunerDetected deliberately false model answers by asking unrelated follow-up questions.
References
- Yarin Gal — Oxford research profileoatml.cs.ox.ac.uk
Substantial early contributions to Bayesian deep learning; uncertainty tools deployed in medicine, robotics and science. Verified live 2026-10-25.
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Reviewed August 9, 2026 · Checked for accuracy and new information.
