Kiri Wagstaff
Kiri Wagstaff develops and studies machine learning for scientific and public problems, including space exploration. Wagstaff received a computer science doctorate from Cornell in 2002. Her thesis, Intelligent Clustering with Instance-Level Constraints, studied clustering that incorporates constraints on individual examples. Wagstaff wrote Machine Learning That Matters in 2012. She recommends it as an account of machine learning’s real-world impact, and she gave an invited AAAI talk on related challenges.
- Works
- 254
- Citations
- 6,121
- h-index
- 34
Publication numbers from OpenAlex, as of 14 October 2026.
Timeline
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2002
Constrained clustering research
Wagstaff received a computer science doctorate from Cornell in 2002. Her thesis, Intelligent Clustering with Instance-Level Constraints, studied clustering that incorporates constraints on individual examples.
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2012
Machine learning impact
Wagstaff wrote Machine Learning That Matters in 2012. She recommends it as an account of machine learning’s real-world impact and gave an invited AAAI talk on related challenges.
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2018
Library collection research
Wagstaff and Geoffrey Z. Liu studied classifiers for predicting which books might be removed from a library collection. Their 2018 paper evaluated several classifiers against librarian decisions on an academic collection.
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2023–2024
AI policy fellowship
Wagstaff served as an AI subject matter expert in the United States Senate through an AAAS Science and Technology Policy Fellowship from 2023 to 2024.
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2023
Research recognition
AAAI elected Kiri Wagstaff as a Fellow in 2023.
Sources and credits
Photo: IPTC Caption: work order 161109 Kiri Wagstaff portrait photog: Dutch Slager; supplied by Kiri Wagstaff. License: Not stated by source. Source: wkiri.com. Cropped to a square and resized. Ask us to remove or replace this photo.