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Priyadarshini Panda

Lloyd F. Hunt Early Career Chair of Electrical & Computer Engineering and Associate Professor of Electrical & Computer Engineering

Education

  • 2019, Doctoral Degree, Purdue University
  • 2012, Master's Degree, Birla Institute of Tech & Science
  • 2012, Bachelor's Degree, Birla Institute of Tech & Science

Biography

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. Her research interests lie in Algorithm-Hardware Co-design for Efficient AI/ML, Neuromorphic Computing and Spiking Neural Networks. She received her Ph.D. from Purdue University in 2019. She received the B.E. degree in Electrical & Electronics Engineering and the M.Sc. degree in Physics from B.I.T.S. Pilani, India, in 2013. She was the recipient of outstanding student award in physics for academic excellence. From 2013-14, she worked in Intel, India on RTL design for graphics power management. She has also worked with Intel Labs, USA, in 2017 and Nvidia, India in 2013 as research intern. During her internship at Intel Labs, 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. Dr. Panda servers on the technical program committees of multiple AI/ML and hardware design conferences such as, DAC, DATE, NeurIPS, ICLR, MICRO among others.

Research Summary

My research focuses on developing algorithmic and hardware design solutions to enable energy-efficient, sustainable, and ubiquitous artificial intelligence (AI). Central to this vision is the integration of nature-inspired principles - efficiency, robustness, and adaptability - into the design of intelligent systems. In the domain of neuromorphic computing, I work on bio-inspired spiking neural networks (SNNs) and emerging compute-in-memory (CiM) hardware accelerators, emphasizing device-circuit-architecture-algorithm co-simulation and cross-layer optimization. Complementing this, my work in efficient machine learning targets compression-friendly algorithm design for Transformers, large language models (LLMs), and foundation models using sparsity, quantization, and input-adaptive computation. These algorithmic advances are co-designed with hardware through system-level integration and acceleration across FPGAs, SoCs, and ASICs.

Awards

  • 2025 IEEE TCAD Donald O. Pederson Best Paper Award
  • 2025 DARPA Director’s Fellowship Award
  • 2025 Google Systems and ML Award (Inaugural)
  • 2025 Semiconductor Research Corporation (SRC) SRC Young Faculty Award
  • 2024 Purdue Engineering 38 under 38 Award (Inaugural)
  • 2024 Asia-South Pacific Design Automation Conference(ASP-DAC) Best Paper Award Nomination
  • 2023 Research featured at the German-American Frontiers of Engineering Symposium organized by the National Academy of Engineering (NAE) and Alexander Humboldt Foundation
  • 2023 DARPA Young Faculty Award
  • 2023 NSF CAREER Award
  • 2022 IEEE Brain Community Best Paper Award
  • 2022 IEEE/ACM International Symposium on Low-Power Electronic and Design (ISLPED) Best Paper Award
  • 2022 DARPA Riser Award
  • 2022 Google Research Scholar Award
  • 2020 Amazon Research Award
Appointments
  • Ming Hsieh Department of Electrical and Computer Engineering
Office
  • EEB 324
  • Hughes Aircraft Electrical Engineering Center
  • 3740 McClintock Ave., Los Angeles, CA 90089
  • USC Mail Code: 2563
Contact Information
  • priya.panda@usc.edu
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