Sanghamitra Dutta is an assistant professor in the Department of Electrical and Computer Engineering at the University of Maryland College Park. Prior to joining UMD, she was a senior research associate at JPMorgan Chase AI Research in the Explainable AI Centre of Excellence (XAI CoE). She received her Ph.D. and Masters from Carnegie Mellon University and B. Tech. from IIT Kharagpur, all in Electrical and Computer Engineering. 

Her research interests broadly revolve around reliable and trustworthy machine learning. She is particularly interested in addressing the challenges concerning fairness, explainability, and law, by bringing in a novel foundational perspective deep-rooted in information theory, causality, and optimization. Her research has been published in both machine learning and information theory venues, featured in New Scientist, and also adopted as part of the fair lending model review at JPMorgan. In her prior work, she has also examined problems in reliable computing, proposing novel algorithmic solutions for large-scale distributed machine learning, using tools from coding theory (an emerging area called “coded computing”). 

She is a recipient of the 2022 Simons Institute Fellowship for Causality, 2021 AG Milnes Outstanding Thesis Award from CMU, 2020 Cylab Presidential Fellowship, 2019 K&L Gates Presidential Fellowship, 2019 Axel Berny Presidential Graduate Fellowship, 2017 Tan Endowed Graduate Fellowship, 2016 Prabhu and Poonam Goel Graduate Fellowship, 2015 Best Undergraduate Project Award at IIT Kharagpur, and the 2014 HONDA Young Engineer and Scientist Award. She has also pursued research internships at IBM Research and Dataminr.


Participation & Position
Research interests
Coding theory
Compressed sensing
Detection and estimation
Pattern recognition
Shannon theory
Signal processing
Statistical learning and inference