Allison Koenecke
Allison Koenecke is an information science researcher whose work applies machine learning and causal inference to questions of algorithmic fairness. She graduated from MIT in 2014, took part in the inaugural Math Prize for Girls, completed a PhD at Stanford, and joined Cornell Information Science after a postdoc at Microsoft Research. Her 2020 study found that five speech recognition systems had an average word error rate of 0.35 for Black speakers and 0.19 for white speakers. Forbes named her to its 30 Under 30 Science list in 2022; in 2025, she coauthored a Nature article on equitable speech translation, won a Sloan Research Fellowship, and joined Cornell Tech. In 2026, she coauthored an article on stakeholder-driven speech audits and received a Cornell Tech teaching award; she is an assistant professor at Cornell Tech.
- Now at
- Cornell University
- Links
- Website, Google Scholar and LinkedIn
Timeline
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2014
MIT and Math Prize for Girls
She graduates from MIT in 2014 with a bachelor's degree in Mathematics with Computer Science and takes part in the inaugural Math Prize for Girls.
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2020
Speech recognition disparities
In 2020, she coauthors a study of five speech recognition systems that finds an average word error rate of 0.35 for Black speakers and 0.19 for white speakers.
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By 2022
Stanford PhD and fairness research
By 2022, she holds a PhD from Stanford's Institute for Computational & Mathematical Engineering. Her research on algorithmic fairness applies machine learning and causal inference to study inequities across online services and public health.
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2022
Postdoc to Cornell
She works as a postdoc in Microsoft Research's Machine Learning and Statistics group and joins Cornell Information Science as an assistant professor in summer 2022.
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2022
Forbes 30 Under 30
In 2022, Forbes selects her for its 30 Under 30 list in Science.
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2025
Speech translation and a Sloan fellowship
In January 2025, she coauthors a Nature article on open-source and equitable speech-to-speech translation. In February 2025, she wins a Sloan Research Fellowship to focus on bias in speech-to-text systems. By October 2025, she is an assistant professor of information science at Cornell Tech.
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2026
AI audits and a teaching award
In March 2026, she coauthors a Nature Machine Intelligence article that argues for stakeholder-driven audits of automatic speech recognition. In 2026, she receives a Cornell Tech Faculty Teaching award.
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As of October 2026
Professor at Cornell Tech
As of October 2026, she is an assistant professor of information science at Cornell Tech and a field faculty member in Computer Science.
Career
- Since 2022Cornell UniversityAssistant Professor, Assistant Professor of Information Science; Field Faculty Member in Computer Science
- Microsoft ResearchPostdoctoral researcher
Education
- 2014Massachusetts Institute of TechnologyBachelor's degree in Mathematics with Computer Science
- Stanford UniversityPhD
Sources and credits
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- Math enthusiasts take aim at STEM glass ceiling
- Computational Math in Industry and Beyond (CME 500) - Winter
- Automated speech recognition and racial bias | EurekAlert!
- Cornell Tech - Allison Koenecke
- Koenecke and Garg selected for Forbes 30 Under 30: Science
- Striving for open-source and equitable speech-to-speech translation
- Two early-career faculty win 2025 Sloan Research awards
- Allison Koenecke Is Making AI Work for Everyone
- The case for stakeholder-driven AI auditing in automatic speech recognition
- Allison Koenecke
