Dr. Alexander Rakhlin

Professor

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Biography

Alexander Rakhlin is a Distinguished Professor in the Department of Brain and Cognitive Sciences at the Massachusetts Institute of Technology (MIT). He is a core member of the MIT Statistics and Data Science Center and the Institute for Data, Systems, and Society (IDSS). Rakhlin’s research focuses on Machine Learning and its intersection with Statistics. He emphasizes the formalization of the learning process, analyzing learning models, and developing algorithmic tools for online prediction. His work addresses the challenges posed by data arriving in a sequential fashion, which is crucial for real-time decision-making in statistical learning frameworks. Rakhlin has a strong academic background with bachelor's degrees in Mathematics and Computer Science from Cornell University and a doctorate from MIT. He completed a postdoctoral fellowship at UC Berkeley in Electrical Engineering and Computer Sciences before joining the University of Pennsylvania as an Associate Professor in the Department of Statistics. He has received multiple awards for his contributions to research and academia, including the NSF CAREER award and the IBM Research Paper award. Rakhlin's recent research interests delve into the understanding of neural networks and interpolation methods, as well as the statistical properties of high-dimensional landscapes arising from fitting complex models to data. His teaching includes courses in Statistical Learning Theory and Mathematical Statistics.

Research Interests

Experience

Distinguished Professor

— Present

Massachusetts Institute of Technology • Cambridge, MA

Lead research in the surface of machine learning and its statistical properties, focusing on the formalization of learning processes and developing new algorithmic tools.

Associate Professor

— Present

University of Pennsylvania • Philadelphia, PA

Contributed to the Department of Statistics and co-directed the Penn Research in Machine Learning (PRiML) center.

Awards

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NSF CAREER Award

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IBM Research Paper Award

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Machine Learning Journal Award

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COLT Paper Award

Courses

Statistical Learning Theory Applications Mathematical Statistics: Non-Asymptotic Approach