Fault Tolerant Distributed Gradient Descent

Nirupam Gupta, a Computer Science Post Doctoral Researcher at EDFL University in Switzerland, joins us today to discuss his work “Byzantine Fault-Tolerance in Peer-to-Peer Distributed Gradient-Descent.” Works Mentioned: Byzantine Fault-Tolerance in Peer-to-Peer Distributed Gradient-Descent by Nirupam Gupta and Nitin H. Vaidya Conference Details:

Guest

Nirupam Gupta: I am a Tenure-Track Assistant Professor in the ML Section of the Department of Computer Science at the University of Copenhagen (DIKU). Before joining DIKU, I was a postdoctoral researcher at EPFL (Switzerland) and Georgetown University (USA). I obtained my PhD from the University of Maryland — College Park and my Bachelor's degree from IIT Delhi. Research. I work on the foundations of trustworthy machine learning, focusing on robustness and privacy in distributed and federated learning. My goal is to make rigorous protection of patients, users and models a practical default in real AI deployments — rather than a guarantee that exists only on paper. A pedagogical introduction to the robustness side of this work is in my book Robust Machine Learning: Distributed Methods for Safe AI (Springer, 2024). Active projects are listed below.