APR 16: Dr. Debarghya Mukherjee, Boston University

“Learning From Data: Two Aspects of Fairness”

Wednesday, April 16, 2025
Hybrid Event
In-person: 801 Massachusetts Avenue
2nd Floor, Room 2128
Boston, MA 02119
12:00-1:00pm Seminar
1:00-2:00pm Luncheon

Register now to participate:

Bio: Dr. Debarghya Mukherjee obtained his Ph.D. under the supervision of Prof. Moulinath Banerjee and Prof. Ya’acov Ritov from the Dept. of Statistics, University of Michigan. Prior to joining BU in Fall 2023, he spent a year as a post-doctoral fellow at Princeton University under the tutelage of Prof. Jianqing Fan. His research interests span a variety of fields: he is keenly interested in the analysis of complex statistical models (e.g. deep neural networks), especially in high dimensions, where the geometry of the problem becomes extremely relevant. Although his previous research has dealt with independent data settings, he is now starting to explore models that capture data dependency (e.g., spatial or temporal dependence under some mixing conditions). He also actively works on algorithmic fairness, domain adaptation, and domain generalization, all of which fall within the purview of constrained classification/regression. One of his key goals is to delve into the connections among these fields of modern machine learning and develop methodologies for the optimal transfer of knowledge from one domain to another while preserving fairness.