Neuromorphic Computing and Engineering
The Neuromorphic Computing research thrust at the Department of Computer Engineering focuses on advances in brain-inspired intelligence through innovations in algorithms, devices, and architectures that emulate the efficiency and adaptability of biological systems. Specific areas of research include
- Spiking neural network (SNN) algorithms and systems
- Continual or lifelong learning models, algorithms, and systems inspired by neuroscience
- Nonvolatile memory-based architecture and chips (e.g. Memristors, FeFETs)
- Emerging device and circuit technologies for edge and extreme environments
- Co-design methodologies and EDA tools for neuromorphic architecture
- Neuromorphic silicon-photonic circuits and mixed-signal designs
- Neuro for AI and AI for Neuro
- Edge applications for NeuroAI (e.g. Robotics, Defense, Medical devices)
UT San Antonio’s neuromorphic computing and engineering research is uniquely interdisciplinary, bringing expertise across computing, psychology, neuroscience, and health sciences.
Computer Engineering faculty works with researchers in psychology and neuroscience that offer deep insights into brain organization, cognition, and learning, informing biologically grounded models that inspire algorithmic and hardware innovations.
Collaborations with health sciences researchers bring application-driven perspectives, targeting neuromorphic solutions for healthcare, rehabilitation, and personalized medicine.
Together, these converging strengths position UT San Antonio as a leader in next-generation neuromorphic systems that blend biological inspiration, emerging devices, and cross-disciplinary applications for defense, healthcare, and intelligent infrastructure.
Faculty Members
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Dhireesha Kudithipudi, PhD (Thrust Lead) Professor, CE & CS Director of MATRIX AI Consortium, Robert F. McDermott Endowed Chair in Engineering Expertise: Neuro-Inspired AI, Neuromorphic Computing, Continual Learning, Energy Efficient AI/ML, AI Accelerators & Robust Infrastructure Email: dk@utsa.edu |
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William Severa, PhD Associate Professor, CS Email: William.Severa@utsa.edu |
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Panagiotis (Panos) Markopoulos, Ph.D. Associate Professor Computer Engineering and Computer Science Cloud Technology Endowed Fellow Expertise: Machine learning theory, algorithms, and systems |
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Assistant Professor Computer Engineering Expertise: AI hardware, Photonic computing, Computer Architecture Email: dharanidhar.dang@utsa.edu |
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