Portrait of Subhabrata (Subho) Mukherjee

Subhabrata (Subho) Mukherjee

Senior Researcher


Leading cross-team and cross-org initiative for [Efficient AI at Scale]. Our focus is on efficient learning of massive neural networks for both model (e.g., neural architecture search, model compression, sparse and modular learning) and data efficiency (e.g., zero-shot and few-shot learning, semi-supervised learning). We develop state-of-the-art computationally efficient models and techniques to enable AI practitioners, researchers and engineers to use large-scale models in practice. Our technologies have been deployed in several enterprise scenarios including Turing, Bing and Microsoft 365.

Honors: 2022 MIT Technology Review Innovators under 35 Semi-finalist (listed in 100 innovators under 35 world-wide) for work on Efficient AI.

Prior to joining MSR, I was leading the information extraction efforts to build the Amazon Product Knowledge Graph. I graduated summa cum laude from the Max Planck Institute for Informatics, Germany with a PhD in 2017. I was awarded the 2018 SIGKDD Doctoral Dissertation Runner-up Award for my thesis on credibility analysis and misinformation. I previously worked at IBM Research on domain adaptation of question-answering systems, sentiment analysis and opinion mining.

Comprehensive list of publications in [Google Scholar] [Semantic Scholar] [DBLP].

Refer to [recent news] for updates!

I have been fortunate to collaborate with several talented PhD interns and researchers. Trying to maintain a list [here].