Dylan Foster
Dylan Foster is a machine learning researcher whose work connects reinforcement learning, interactive decision making, and foundation-model training. He earned bachelor's and master's degrees in electrical engineering at USC in 2014, completed a computer science PhD at Cornell in 2019, and won COLT paper awards in 2018 and 2019. He was a postdoctoral fellow at MIT and coauthored a 2023 monograph with Alexander Rakhlin on the statistical foundations of reinforcement learning and interactive decision making. As of October 2026, he is a principal researcher at Microsoft Research and is set to join UC Berkeley as an assistant professor in EECS and Statistics in January 2027.
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Timeline
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2014
Electrical engineering at USC
He earns BS and MS degrees in electrical engineering from the University of Southern California in 2014.
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2018
A COLT student paper award
He and Karthik Sridharan win COLT's Best Student Paper Award in 2018.
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2019
A Cornell PhD and awards
He completes a PhD in computer science at Cornell in 2019, advised by Karthik Sridharan. His paper Orthogonal Statistical Learning earns COLT's Best Paper Award in 2019. Cornell Computer Science gives him its Doctoral Dissertation Award in 2019.
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2021
Postdoctoral work at MIT
In 2021, he is a postdoctoral fellow at the MIT Institute for Foundations of Data Science.
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2023
A reinforcement learning monograph
With Alexander Rakhlin, he publishes Foundations of Reinforcement Learning and Interactive Decision Making as a 2023 preprint. The monograph gives a statistical view of interactive decision making across bandits and reinforcement learning with function approximation.
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2026
Coverage profiles for post-training
At a January 2026 seminar, he introduces the coverage profile—the probability mass a model places on high-quality outputs—as a statistical quantity for foundation-model post-training success.
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As of October 2026
Principal researcher at Microsoft
In October 2026, he is a principal researcher at Microsoft Research, New England and New York City. He is set to join UC Berkeley as an assistant professor in EECS and Statistics in January 2027.
Sources and credits
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- Dylan Foster
- Machine Learning at Cornell
- Machine Learning and Friends Lunch: Dylan Foster, Understanding the foundation model pipeline: From imitation to exploration
- Publications - Dylan Foster
- SCS Seminar Talk: Dylan Foster | College of Computing
- Foundations of Reinforcement Learning and Interactive Decision Making
- Statistics and Data Science Seminar - Dylan Foster | Carnegie Mellon University Computer Science Department
- Dylan Foster at Microsoft Research