Rahul Mazumder

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Rahul Mazumder

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Rahul Mazumder is the Nanyang Technological University Associate Professor of Operations Research and Statistics and an Associate Professor of Operations Research and Statistics at the MIT Sloan School of Management.

Prior to joining MIT, he was an Assistant Professor in the Department of Statistics, Columbia University from Fall 2013 through June 2015, and was also affiliated with the Data Science Institute, Columbia University.  Prior to that, Rahul was a PostDoctoral Associate at MIT from 2012 - 2013.

His research interests are in data science, statistical machine learning, large scale optimization, mathematical programming; and in particular, their interplay. He is also interested in "big data" applications in environmental and climate studies, social science, and recommender systems. He has published in a variety of journals:  Journal of Machine Learning Research, Annals of Statistics, Journal of the American Statistical Association,and Annals of Applied Statistics, among others.

Rahul completed his BS and MS in statistics from the Indian Statistical Institute, Kolkata in 2007. He received his PhD in statistics from Stanford University in 2012.

Honors

Mazumder wins 2024 Leo Breiman Junior Award

March 8, 2024

Mazumder wins early career award

February 23, 2024

INFORMS honors Mazumder

Mazumder’s research honored by Office of Naval Research

Mazumder wins INFORMS prize

Publications

"Grouped Variable Selection with Discrete Optimization: Computational and Statistical Perspectives."

Hazimeh, Hussein, Rahul Mazumder, and Peter Radchenko. Annals of Statistics. Forthcoming.

"Integration of Survival Data from Multiple Studies."

Ventz, Steffen, Rahul Mazumder, and Lorenzo Trippa. Biometrics. Forthcoming.

"Solving L1-regularized SVMs and Related Linear Programs: Revisiting the Effectiveness of Column and Constraint Generation."

Dedieu, Antoine, Rahul Mazumder, and Haoyue Wang. Journal of Machine Learning Research. Forthcoming.

"Subset Selection with Shrinkage: Sparse Linear Modeling when the SNR is Low."

Mazumder, Rahul, Peter Radchenko, and Antoine Dedieu. Forthcoming.

"Using L1-relaxation and Integer Programming to Obtain Dual Bounds for Sparse PCA."

Dey, Santanu, Rahul Mazumder, and Guanyi Wang. Operations Research. Forthcoming.

"Sparse Regression at Scale: Branch-and-Bound rooted in First-Order Optimization."

Hazimeh, Hussein, Rahul Mazumder, and Ali Saab. Mathematical Programming (2021).

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