Dhireesha Kudithipudi

Dhireesha Kudithipudi is a Professor in the Department of Computer Science at the University of Texas at San Antonio (UTSA) and Director of the MATRIX AI Consortium. Her work focuses on advancing neuromorphic computing, energy-efficient machine learning architectures, and lifelong learning systems. She holds a Ph.D. in Electrical and Computer Engineering from UTSA and an M.S. in Computer Engineering from Wright State University.

Her research interests include AI algorithms, neuromorphic hardware design, spiking neural networks, and memristor-based systems. She leads initiatives in neuromorphic benchmarking (NeuroBench), energy-efficient computing roadmaps (EES2), and collaborative frameworks like the Neuromorphic Commons (THOR). Her lab develops neuromorphic chips with on-device learning capabilities, such as the Genesis chip, and explores applications in edge computing.

Dr. Kudithipudi has pioneered techniques for continual learning in spiking networks, probabilistic metaplasticity, and low-precision numerical formats (e.g., PositCL). Her work bridges theoretical neuroscience principles with practical hardware implementations, emphasizing sustainability and scalability. She also contributes to NSF-funded projects like EFRI BRAID and NAIAD, advancing interdisciplinary AI research.

Her lab’s collaborations include developing the NeuroBench framework for fair benchmarking and exploring neuromorphic systems for tasks like video/activity recognition and time-series forecasting. She advises on hardware-software co-design strategies for efficient neural network deployment on constrained devices.