Dr. Saurav Prakash
IIT Madras
Location: TII Yas Auditorium
13th February 2025, 02:00pm – 03:00pm (GST)
| Title: | Efficient training of large models at the edge |
| Abstract: | The rapid growth of edge devices has created a dynamic, AI-powered data ecosystem with significant potential for societal advancement. However, privacy concerns restrict data sharing across multiple owners, hindering the full potential of AI. Furthermore, edge devices often have substantial resource constraints and heterogeneity, severely restricting their ability to handle large models. This talk will provide innovative solutions to overcome these challenges and enable efficient and privacy-preserving ML in diverse edge settings. As a key highlight, we will address the following question: How to enable federated learning of a large global model, when each edge device has the capability to locally train a relatively much smaller model? |
| Bio: | Dr. Saurav Prakash is an Assistant Professor in the Department of Electrical Engineering (EE) at IIT Madras and affiliated with the Center for Responsible AI (CeRAI). He received his BTech in EE from IIT Kanpur in 2016 and completed his PhD in EE at the University of Southern California (USC) in 2022. Afterwards, he was a postdoctoral researcher at the University of Illinois Urbana-Champaign (UIUC) for a couple of years before joining IIT Madras. His research interests span Information and Coding Theory, Machine Unlearning, Federated Learning, and Hyperbolic Geometry. Among his accolades, he was one of the recipients of the Qualcomm Innovation Fellowship in 2021 and was one of the Viterbi-India Fellows in summer 2015. He is currently visiting MBZUAI in the ML department, hosted by Dr. Praneeth Vepakomma.
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