Andrew M. Bean
Also known as Andrew Bean, Andrew Michael Bean
Andrew M. Bean studies cooperation between people and AI and how language models should be evaluated. He earned a BSc in Applied Mathematics at Yale in 2017, developed fixed-income algorithms at Bridgewater, and later worked in data science, completed an Oxford MSc, taught AI ethics at Stanford, and trained a custom LLM at Thomson Reuters. His research includes LingOly, a multilingual reasoning benchmark; PRISM, a dataset of human preferences and LLM feedback that won NeurIPS 2024's Best Paper Award in Datasets and Benchmarks; and a review that found problems with LLM benchmark validity. In 2026, he coauthored a randomized study of medical chatbots and is a DPhil student at Oxford and a Senior Researcher in the Thomson Reuters–Imperial Frontier AI Research Lab.
- Now at
- HealthSherpa
- Badges
- Links
- Website, Google Scholar, LinkedIn and GitHub
Timeline
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2017–2021
Yale mathematics and Bridgewater
He earns a BSc in Applied Mathematics at Yale in 2017. From 2017 to 2021, he works as an investment associate at Bridgewater Associates and develops proprietary algorithms for fixed-income markets.
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2021
Machine learning at HealthSherpa
In 2021, he works as a data science consultant at HealthSherpa and trains machine-learning models to assess investment opportunities.
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2022
An Oxford MSc thesis
He completes an MSc in Social Data Science at Oxford's Internet Institute in 2022. His thesis, Teaching AI to Cooperate with Human Partners through Rule-based Play, studies rule-based cooperation between people and AI.
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2023–2025
Stanford teaching and Thomson Reuters
From 2023 to 2025, he teaches at Stanford's Bing Overseas Study Program and designs an undergraduate course on AI ethics. In 2025, he joins Thomson Reuters' Foundational Research team as a research scientist intern and trains a custom LLM for client applications.
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June 2024
LingOly tests language reasoning
In June 2024, he coauthors LingOly, a benchmark of 1,133 puzzles across more than 90 mostly low-resource languages. It tests LLMs on linguistic patterns and complex task instructions; the top model reaches 38.7% on harder problems.
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December 2024
PRISM wins a NeurIPS award
In December 2024, he coauthors PRISM, a dataset linking preferences and feedback from 1,500 people in 75 countries to 8,011 conversations with 21 LLMs. It wins NeurIPS 2024's Best Paper Award in the Datasets and Benchmarks track.
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November 2025
Reviewing LLM benchmarks
In November 2025, he coauthors a systematic review of 445 LLM benchmarks with 29 expert reviewers. The team finds patterns in measured phenomena, tasks and scoring metrics that undermine benchmark claims.
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As of October 2026
DPhil student and lab researcher
He has been a DPhil student in Social Data Science at Oxford's OII since October 2022, studying cooperative AI. In February 2026, he coauthors a randomized study of medical chatbots with 1,298 UK participants selected to represent the adult population; chatbot users identify conditions in less than 34.5% of cases and the right course of action in less than 44.2%. As of October 2026, he is a Senior Researcher in the Thomson Reuters–Imperial Frontier AI Research Lab, working on LLM evaluation, construct validity and algorithmic bias.
Career
- From 2025Thomson ReutersResearch scientist intern
- 2023–2025Stanford University
- From 2021HealthSherpaData science consultant
- 2017–2021Bridgewater AssociatesInvestment associate
Education
- 2022University of OxfordMSc in Social Data Science
- From 2022University of OxfordDPhil student in Social Data Science
- 2017Yale UniversityBSc in Applied Mathematics
Sources and credits
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- cv | Andrew M. Bean
- OII | Andrew Bean
- OSPOXFRD 85: Practical Ethics for Artificial Intelligence (Way: ER) | Stanford in Oxford
- LINGOLY: A Benchmark of Olympiad-Level Linguistic Reasoning Puzzles in Low-Resource and Extinct Languages
- Andrew M. Bean
- NeurIPS 2024 Awards
- Measuring what Matters: Construct Validity in Large Language Model Benchmarks
- OII | New study warns of risks in AI chatbots giving medical advice
- Reliability of LLMs as medical assistants for the general public: a randomized preregistered study
- People | Research groups | Imperial College London
