Arya Mazumdar

Interests

Error Correcting Codes, Information Theory, Statistical Reconstruction, Distributed Optimization

Research

Arya's research in error-correcting codes has produced the first efficiently implementable family of codes over permutations, as well as the best known fundamental limits of locally repairable codes for distributed storage. Arya's current research interests include recent advances of statistical machine learning in the application domains of interactive learning algorithms, statistical reconstructions, community detection and distributed optimization. Arya is also very much interested in fundamental problems that involve trade-offs between communication and computation in distributed settings. 

Biography

Before coming to the University of Massachusetts Amherst, Arya was an assistant professor at the University of Minnesota. He received his Ph.D. degree from the University of Maryland, College Park, in 2011. Followed by this, he was a postdoctoral scholar at the Massachusetts Institute of Technology (2011-2012). Arya has spent time in tech industries in the past, including in Amazon AI and Search, HP Labs, and IBM Almaden Research Center.

Activities & Awards

Arya is a recipient of the 2015 NSF CAREER award, the 2020 EURASIP JASP Best Paper Award,  and the 2010 IEEE ISIT Jack K. Wolf Paper Award. He is also a recipient of the 2011 Distinguished Dissertation Fellowship Award from the University of Maryland.  Arya's works have been regularly appearing in the top venues of information theory and machine learning, multiple times as spotlight papers. Arya is an associate editor of IEEE Transactions on Information Theory and an area editor of Now Publishers Foundation and Trends Series.