Computer Architecture and VLSI

The Computer Architecture research thrust at the Department of Computer Engineering focuses on building the next generation of computing systems—from nanoscale circuits to exascale architectures—that will power the data-intensive and AI-driven world of tomorrow. Our researchers address challenges across the full hardware–software stack, exploring innovations in:

  • Processor microarchitecture: energy-efficient system design, system-level simulation.
  • Memory and storage systems: advanced cache management, near-memory and in-memory computing, non-volatile memory hierarchies, and memory security.
  • Interconnects and on-chip networks: low-latency, high-bandwidth communication fabrics (such as silicon photonics) spanning manycore, heterogeneous, and chiplet-based systems.
  • CAD and EDA methodologies: design automation tools for performance, reliability, and thermal-aware chip design; co-optimization of hardware and algorithms.
  • Low-power VLSI Design.
  • Emerging computing paradigms: Photonic computing for AI, Memristor-based in-memory computing.

Together, these areas define a cohesive vision for architectural innovation in the post-Moore, post-CMOS era, where performance gains will come not from transistor scaling, but from co-design across devices, circuits, architecture, and software. With strong partnerships in academia, national labs, and industry, our work prepares the next generation of engineers to shape the future landscape of computing—from edge to cloud to photonic data centers.

Faculty Members

 

 

faculty

Eugene John (Thrust Lead)

Professor

Computer Engineering

Expertise: Energy Efficient Computing, AI/ML,  AI Hardware, Flexible Electronics, AI Workload Analysis and Characterization, Computer Architecture and Performance Evaluation, Low Power VLSI Design, Ultra-Low Energy Computing for Implantable Cardiac Devices, Power-Aware and Secure Systems.

Email: eugene.john@utsa.edu

 

 

 

faculty

Dharanidar (DD) Dang, Ph.D. (Thrust Co-lead)

Assistant Professor

Computer Engineering

Expertise: AI hardware, Photonic computing, Computer Architecture, AI Accelerator, Thermal Management

Email: dharanidhar.dang@utsa.edu

 

faculty

Dhireesha Kudithipudi, PhD

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

 

 

 

 

 

Affiliate Faculty Members

TBD

 

Research Institutes, Centers, and Laboratories