Event Details

Artificial Intelligence (AI) is poised to revolutionize society, yet its escalating energy demands pose a formidable challenge to its long-term sustainability. The staggering gap in energy consumption between biological (Human Brain @20watts) and artificial intelligence (ChatGPT @100KWatts) is striking. My research aims to bridge this gap with a bio-inspired, integrative approach, where algorithm-architecture-and-system co-design and neuromorphic computing converge to create intelligent, energy-efficient systems. In this talk, I will present my group’s recent efforts towards enabling low-precision and sparse machine intelligence design, simulation, and evaluation across different applications. I will also discuss dataflow modifications and packing techniques that yield significantly reduced data transfer overhead for efficient execution of LLMs on edge devices.

December 5, 2025

Join Zoom Webinar

Host: Steve Crago
POC: Amy Kasmir

Speaker Bio

Dr. Priya Panda is an Associate Professor in the Electrical & Computer Engineering Department at the University of Southern California starting Fall 2025. Prior to her appointment at USC, she was an Assistant Professor at Yale University in the Electrical & Computer Engineering department from 2019-2025. Dr. Panda has been a Visiting Faculty Researcher at Google DeepMind in 2024-25.She received her B.E. and Master's degree from BITS, Pilani, India in 2013 and her Ph.D. from Purdue University, USA in 2019. During her PhD, she interned in Intel Labs where she developed large scale spiking neural network algorithms for benchmarking the Loihi chip. She is the recipient of the 2019 Amazon Research Award, 2022 Google Research Scholar Award, 2022 DARPA Riser Award, 2023 NSF CAREER Award, 2023 DARPA Young Faculty Award, the inaugural 2024 Purdue Engineering 38 under 38 award, 2025 Google Systems and ML Award and 2025 DARPA Director’s Fellowship Award. Her group's research has also received the 2022 ISLPED Best Paper Award, 2022 IEEE Brain Community Best Paper Award, 2024 ASP-DAC Best Paper Nomination and 2025 IEEE TCAD Donald O. Pederson Best Paper Award. Her research interests lie in Neuromorphic Computing, and Efficient AI.