Bio-Inspired Algorithm & Hardware Co-Design for Efficient AI | Dr. Priya Panda | JHU-IITD SMaRT

This talk is part of the Scientific Machine Learning Research Talks (SMaRT) Seminar Series, a joint initiative between Johns Hopkins University and IIT Delhi.

🔹 Speaker:
Dr. Priya Panda
Associate Professor, Department of Electrical & Computer Engineering
University of Southern California, USA

🔹 Talk Title:
Biologically Inspired Algorithm and Hardware Co-Design for Efficient Machine Intelligence

🔹 Date: Wednesday, October 15, 2025
Time: 7:30 PM IST | 2:00 PM GMT | 10:00 AM EDT

📄 Abstract

Artificial Intelligence (AI) is transforming modern technology but at an immense energy cost, far exceeding that of biological systems — the human brain operates at ~20 watts, while large AI models can demand over 100 kilowatts. Bridging this gap between biological efficiency and artificial computation is the focus of this talk.

Dr. Panda will present her group’s bio-inspired, integrative approach that combines algorithm-hardware co-design and neuromorphic computing to enable intelligent, energy-efficient systems. The talk will explore: (a) Advances in Spiking Neural Networks (SNNs) and their temporal dynamics for robust, low-latency, and energy-efficient computation, (b)Hardware strategies for accelerating SNNs on general-purpose platforms through memory and sparsity management, and (c) Novel techniques such as input-aware dynamic temporal exit and scaling-free quantization for efficient weight and activation compression. Together, these developments chart a path toward sustainable, scalable, and democratized spike-based machine intelligence.

👤 About the Speaker

Dr. Priya Panda is an Associate Professor in the Department of Electrical & Computer Engineering at the University of Southern California (USC), joining in Fall 2025. Prior to USC, she was an Assistant Professor at Yale University (2019–2025) and a Visiting Faculty Researcher at Google DeepMind (2024–2025). Her research focuses on algorithm-hardware co-design, neuromorphic computing, and spiking neural networks for energy-efficient AI/ML systems. She earned her Ph.D. from Purdue University (2019) and B.E. & M.E. degrees from BITS Pilani (2013).

Dr. Panda’s outstanding contributions have been recognized with numerous honors, including: NSF CAREER Award (2023), DARPA Young Faculty Award (2023) and Director’s Fellowship (2025), Google Research Scholar Award (2022) and Systems & ML Award (2025), Amazon Research Award (2019) and DARPA Riser Award (2022), and Multiple Best Paper Awards (ISLPED 2022, IEEE Brain 2022, IEEE TCAD 2025)

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