Rahul Mazumder

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.

Rahul Mazumder is a researcher at the Massachusetts Institute of Technology, specializing in Statistics, Mathematical Programming, Machine Learning, and AI. His work focuses on developing optimization-based methods for high-dimensional data analysis, including techniques for matrix completion, sparse regression, and graphical models. He has contributed to advancements in spectral regularization, low-rank matrix recovery, and combinatorial optimization for machine learning. His research emphasizes scalable algorithms for problems such as subset selection, covariance thresholding, and differentiable selection in multi-task learning. Mazumder's publications often integrate modern optimization techniques with statistical modeling to address challenges in large-scale data analysis.