Priya Panda

Priya Panda serves as an Assistant Professor in the Electrical Engineering Department at Yale University, where she directs the Intelligent Computing Lab. Her academic foundation includes a Ph.D. from Purdue University completed in 2019.

Educational background:

• Ph.D. in Electrical Engineering or related field from Purdue University (2019)

Her research program centers on neuromorphic computing and the development of robust, energy-efficient machine intelligence systems. She investigates hardware-software co-design approaches to deploy AI on resource-constrained devices while maintaining resilience against adversarial perturbations and optimizing power consumption. This work bridges neuroscience-inspired architectures with practical deep learning applications.

Analysis of her publication record reveals a dominant focus on energy efficiency in deep learning, with recurring methodologies including quantization, pruning, and spiking neural networks. Her research consistently targets hardware-aware AI implementation, demonstrating how activation density metrics and noise sensitivity can drive optimization in neural network deployment.

Scientific recognition includes:

• 2019 Amazon Research Award for innovative contributions to energy-efficient machine learning

As director of Yale's Intelligent Computing Lab, she leads a research ecosystem focused on sustainable AI development. Her team's work addresses critical challenges in edge computing and large-scale data centers where energy constraints fundamentally shape system design. Current efforts emphasize creating deployable AI solutions that maintain robustness without compromising efficiency.