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Priyadarshini Panda is an Associate Professor in the Ming Hsieh Department of Electrical and Computer Engineering at the University of Southern California. Her research focuses on algorithm-hardware co-design for energy-efficient and sustainable artificial intelligence, particularly in neuromorphic computing and spiking neural networks. Panda's work integrates nature-inspired principles to design intelligent systems that prioritize efficiency, robustness, and adaptability. She has a diverse background in electrical engineering and has contributed to the development of large-scale algorithms for emerging compute-in-memory hardware accelerators. She has received numerous awards, including the 2023 NSF CAREER Award and the 2025 DARPA Director’s Fellowship Award, recognizing her significant contributions to AI and machine learning hardware. Panda has also served on technical program committees for multiple leading AI/ML hardware design conferences.
GRE is NOT required for Master's applicants for 2025-2026.