Sanghamitra Dutta (B. Tech. IIT Kharagpur) is a Ph.D. candidate at Carnegie Mellon University, USA, expected to graduate in May 2021. Her research interests revolve around machine learning, information theory, causality, and statistics. She is currently focused on addressing the emerging reliability issues in machine learning concerning fairness, explainability, and law with recent publications at AAAI'20, ICML'20 (also featured in New Scientist and CMU Engineering News). She is planning to join the Department of Electrical and Computer Engineering at the University of Maryland, College Park as an Assistant Professor.
In her prior work, she has also examined problems in reliable computing, proposing novel algorithmic solutions for large-scale distributed machine learning in the presence of faults and failures, using tools from coding theory (an emerging area called “coded computing”). Her results on coded computing address problems that have been open for several decades and have received substantial attention from across communities (published at IEEE Transactions on Information Theory’19,’20, NeurIPS’16, AISTATS’18, IEEE BigData’18, ICML Workshop Spotlight’19, ISIT’17,’18, Proceedings of IEEE’20 along with two pending patents).
She is a recipient of the 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, the 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.
- Causality, Spring 2022. Research Fellow.