Rahul Mazumder


Rahul Mazumder


Rahul Mazumder is the Robert G. James Career Development Professor and 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.


Mazumder wins INFORMS prize

Mazumder’s research honored by Office of Naval Research


"A Computational Framework for Multivariate Convex Regression and its Variants."

Mazumder, Rahul, Arkopal Choudhury, Garud Iyengar, and Bodhisattva Sen. Journal of the American Statistical Association. Forthcoming.

"Computation of the Maximum Likelihood Estimator in Low-rank Factor Analysis."

Khamaru, Koulik, and Rahul Mazumder. Mathematical Programming. Forthcoming. arXiv Preprint.

"Learning a Mixture of Gaussians via Mixed Integer Optimization."

Bandi, Hari, Dimitris Bertsimas, and Rahul Mazumder. INFORMS Journal on Optimization. Forthcoming.

"Fast Best Subset Selection: Coordinate Descent and Local Combinatorial Optimization Algorithms."

Hazimeh, Hussein and Rahul Mazumder. Operations Research Vol. 68, No. 5 (2020): 1517-1537.

"Hierarchical Modeling and Shrinkage for User Session Length Prediction in Media Streaming."

Antoine Dedieu, Rahul Mazumder, Zhen Zhu, and Hossein Vahabi. In Proceedings of the 27th International Conference on Information and Knowledge (CKIM 2018), Turin, Italy: October 2018.

"Flexible Low-rank Statistical Modeling with Missing Data and Side Information."

Fithian, William, and Rahul Mazumder. Statistical Science Vol. 33, No. 2 (2018): 238-260. arXiv Preprint.

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