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Mikhail Belkin

Professor
Photo of Mikhail Belkin

Biographical Info

Mikhail Belkin received his Ph.D. in 2003 from the Department of Mathematics at the University of Chicago. His research interests are in theory and  applications of machine learning and data analysis. Some of his well-known work includes widely used Laplacian Eigenmaps, Graph Regularization and Manifold Regularization algorithms, which brought ideas from classical differential geometry and spectral analysis to data science. His recent work has been concerned with understanding remarkable mathematical and statistical phenomena observed in deep learning. This empirical evidence necessitated revisiting some of the basic concepts in statistics and optimization.  One of his key recent findings is the “double descent” risk curve that extends the textbook U-shaped bias-variance trade-off curve beyond the point of interpolation.

Mikhail Belkin is a recipient of a NSF Career Award and a number of best paper and other awards. He has served on the editorial boards of the Journal of Machine Learning Research, IEEE Pattern Analysis and Machine Intelligence and SIAM Journal on Mathematics of Data Science.

Website: misha.belkin-wang.org

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Mike Holst

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Lucila Ohno-Machado

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Rob Knight

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Lily Weng

Assistant Professor
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Berk Ustun

Assistant Professor
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Frank Wuerthwein

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Benjamin Smarr

Assistant Professor
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Eran Mukamel

Assistant Professor

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Executive Office

Mikhail Belkin

Professor
Photo of Mikhail Belkin

Biographical Info

Mikhail Belkin received his Ph.D. in 2003 from the Department of Mathematics at the University of Chicago. His research interests are in theory and  applications of machine learning and data analysis. Some of his well-known work includes widely used Laplacian Eigenmaps, Graph Regularization and Manifold Regularization algorithms, which brought ideas from classical differential geometry and spectral analysis to data science. His recent work has been concerned with understanding remarkable mathematical and statistical phenomena observed in deep learning. This empirical evidence necessitated revisiting some of the basic concepts in statistics and optimization.  One of his key recent findings is the “double descent” risk curve that extends the textbook U-shaped bias-variance trade-off curve beyond the point of interpolation.

Mikhail Belkin is a recipient of a NSF Career Award and a number of best paper and other awards. He has served on the editorial boards of the Journal of Machine Learning Research, IEEE Pattern Analysis and Machine Intelligence and SIAM Journal on Mathematics of Data Science.

Website: misha.belkin-wang.org

Related by Category

Photo of Mike Holst

Mike Holst

Professor
Photo of Lucila Ohno-Machado

Lucila Ohno-Machado

Professor
Photo of Rob Knight

Rob Knight

Founding Director, Center for Microbiome Innovation; Professor, Pediatrics and Computer Science & Engineering
Photo of Lily Weng

Lily Weng

Assistant Professor
Photo of Berk Ustun

Berk Ustun

Assistant Professor
Photo of Frank Wuerthwein

Frank Wuerthwein

Professor
Photo of Benjamin Smarr

Benjamin Smarr

Assistant Professor
Photo of Eran Mukamel

Eran Mukamel

Assistant Professor

Communications

Mikhail Belkin

Professor
Photo of Mikhail Belkin

Biographical Info

Mikhail Belkin received his Ph.D. in 2003 from the Department of Mathematics at the University of Chicago. His research interests are in theory and  applications of machine learning and data analysis. Some of his well-known work includes widely used Laplacian Eigenmaps, Graph Regularization and Manifold Regularization algorithms, which brought ideas from classical differential geometry and spectral analysis to data science. His recent work has been concerned with understanding remarkable mathematical and statistical phenomena observed in deep learning. This empirical evidence necessitated revisiting some of the basic concepts in statistics and optimization.  One of his key recent findings is the “double descent” risk curve that extends the textbook U-shaped bias-variance trade-off curve beyond the point of interpolation.

Mikhail Belkin is a recipient of a NSF Career Award and a number of best paper and other awards. He has served on the editorial boards of the Journal of Machine Learning Research, IEEE Pattern Analysis and Machine Intelligence and SIAM Journal on Mathematics of Data Science.

Website: misha.belkin-wang.org

Related by Category

Photo of Mike Holst

Mike Holst

Professor
Photo of Lucila Ohno-Machado

Lucila Ohno-Machado

Professor
Photo of Rob Knight

Rob Knight

Founding Director, Center for Microbiome Innovation; Professor, Pediatrics and Computer Science & Engineering
Photo of Lily Weng

Lily Weng

Assistant Professor
Photo of Berk Ustun

Berk Ustun

Assistant Professor
Photo of Frank Wuerthwein

Frank Wuerthwein

Professor
Photo of Benjamin Smarr

Benjamin Smarr

Assistant Professor
Photo of Eran Mukamel

Eran Mukamel

Assistant Professor