Emma Brunskill
Emma Brunskill studies how AI can learn from limited experience to make useful decisions. Her research is motivated by applications in education and healthcare. Brunskill previously held an assistant professorship at Carnegie Mellon and an academic research role at Stanford. Her goal is building AI that learns from few samples and makes robust decisions. Her laboratory’s application areas include healthcare and education.
- Works
- 264
- Citations
- 7,985
- h-index
- 41
Publication numbers from OpenAlex, as of 14 October 2026.
Timeline
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2021–2024
Education research advice
She participated in an informal Khan Academy research advisory committee from 2021 to 2024.
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2023
A machine learning conference
Brunskill served as co-program chair of ICML 2023.
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2025
Research recognition
AAAI elected Emma Brunskill as a Fellow in 2025.
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As of October 2026
Research across universities
Brunskill previously held an assistant professorship at Carnegie Mellon and an academic research role at Stanford.
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As of October 2026
Learning from limited samples
She aims to building AI that learns from few samples and makes robust decisions. Her laboratory’s application areas include healthcare and education.
Sources and credits
Photo: Jess Alvarenga. License: Not stated by source. Source: cs.stanford.edu. Cropped to a square and resized. Ask us to remove or replace this photo.