AI Tennessee

fundamentals of ai

Developing the components that make AI intelligent and impactful

Chris Howard, HPSC account manager, pulls a server for inspection at the High Performance Scientific Computing’s ISAAC (Infrastructure for Scientific Applications and Advanced Computing) data center on at the University of Tennessee, Knoxville.
Detail macro photo of components inside a server at the High Performance Scientific Computing’s ISAAC (Infrastructure for Scientific Applications and Advanced Computing) data center at the University of Tennessee, Knoxville.
Alexis McCraw, 3rd year Phd student in Experimental Psychology, reads eye movements and brain waves of a minor in order to gain a better understanding of different aspects of child development in the Attention, Brain, and Cognition Lab in the Austin Peay Building at the University of Tennessee, Knoxville.

The benefits AI provides to industrial and personal applications are the proverbial tip of the iceberg. The future of AI is much bigger—and UT researchers are pursuing a once-in-a-generation opportunity to shape that future as they develop fundamental computing theories, hardware, statistical models, and machine learning algorithms that drive AI’s capabilities.  

Through interdisciplinary collaboration, we’re closing the gap between human and artificial intelligence, advancing neuromorphic and quantum computing, and increasing the efficiency and trustworthiness of AI. Together, we’re preparing AI to be used in new ways to achieve our shared goal: making life and lives better.

Detail macro photo of components at the High Performance Scientific Computing’s ISAAC (Infrastructure for Scientific Applications and Advanced Computing) data center at the University of Tennessee, Knoxville.

UT’s Approach

At UT, researchers are reinventing computing as the engine for the next wave of AI breakthroughs. From advancing quantum architectures that tackle complex optimization problems to pioneering neuromorphic computing inspired by the human brain, they are pushing the boundaries of what machines can learn and do. Members of UT’s foundational AI faculty cluster are tackling core challenges while building the mathematical frameworks that accelerate discovery in areas such as materials, health, energy, and life sciences. The impact is tangible: new algorithms that stage cancer more efficiently, socially assistive robots that support dementia care, and AI-driven tools that improve agricultural productivity. 

“UT has one of the largest neuromorphic computing research efforts in the US, and we’re one of the only ‘full stack’ teams. Our team designs everything: materials, hardware, new AI algorithms, all the way up to the connections to specific applications. This means our new AI concepts inform the hardware, and the hardware we develop helps us innovate new AI concepts.”

—Catherine Schuman, Assistant Professor of Electrical Engineering and Computer Science

James R. Couper, 2nd year grad student in experimental psychology/neuroscience and behavior, reads eye movements and brain waves to gain better understanding of different aspects of child development in the Attention, Brain, and Cognition Lab in the Austin Peay Building at the University of Tennessee, Knoxville.
Chris Howard, HPSC account manager, inspects a server at the High Performance Scientific Computing’s ISAAC (Infrastructure for Scientific Applications and Advanced Computing) data center at the University of Tennessee, Knoxville.
Detail macro photo of a LTO tape machine working at the High Performance Scientific Computing’s ISAAC (Infrastructure for Scientific Applications and Advanced Computing) data center at the University of Tennessee, Knoxville.
Chris Howard, HPSC account manager, inspects a server rack at the High Performance Scientific Computing’s ISAAC (Infrastructure for Scientific Applications and Advanced Computing) data center at the University of Tennessee, Knoxville.
Detail macro photo of components inside a server at the High Performance Scientific Computing’s ISAAC (Infrastructure for Scientific Applications and Advanced Computing) data center at the University of Tennessee, Knoxville

Highlights

Catherine Schumann helping students in her Neomorphic Computing Lab.

Schuman, TENNLab, and UT Research Foundation’s Breakthroughs in Neuromorphic Computing

The TENNLab Neuromorphic Computing Research Group has pioneered spiking neural network architectures and patented multiple brain-inspired computing solutions. Catherine Schuman is part of a $4 million National Science Foundation grant to increase access to neuromorphic technology.

Learn more about advances in neuromorphic computing.

Garrett Rose, Electrical Engineering and Computer Science Professor at the University of Tennessee, Knoxville

Making AI Sleep More Like Humans

Garrett Rose brings neuromorphic computing expertise to an interdisciplinary team that was awarded a $2 million National Science Foundation grant to bridge the gap between human brain processing efficiency and the limitations of current AI models. 

Learn about this research.

Hairong Qi, a Gonzalez Family Professor in the Min H. Kao Department of Electrical Engineering and Computer Science, works with students.

Leading Foundational AI Collaboration Through Faculty Cluster Initiatives

Faculty cluster hiring initiatives are building UT’s AI expertise and infrastructure for transdisciplinary collaboration. All seven clusters integrate AI, and one—the foundational AI cluster—is dedicated to closing the gap between human and artificial intelligence with solutions inspired by neuroscience.  

Learn about computer science faculty in this cluster.

Rebekah Herrman

Laying the Foundations for Quantum Computing

Rebekah Herrman’s research in quantum algorithms demonstrates how quantum computers could change the world—including accelerating AI. She and her colleagues are working on mathematical proofs that help guide further research on quantum computing hardware.  

Learn about quantum computing research.

Chris Howard, HPSC account manager, inspects a server at the High Performance Scientific Computing’s ISAAC (Infrastructure for Scientific Applications and Advanced Computing) data center at the University of Tennessee, Knoxville.

Facilities & Initiatives

UT researchers study, develop, and refine the building blocks of AI in state-of-the-art facilities on and off campus. Centers and research groups receive support from and partner with organizations such as the National Science Foundation, the US Department of Energy, and the Air Force Research Laboratory. 

Aerial photo of the Institute of Advanced Materials and Manufacturing at the University of Tennessee Research Park.

Researchers

  • Aaron Buss

    Aaron Buss

    Associate Professor, Psychology

    Executive function, cognitive development, cognitive neuroscience, computational neuroscience

  • Hairong Qi.

    Hairong Qi

    Gonzalez Family Professor, Electrical Engineering & Computer Science

    Dynamical system analysis, multisensory integration, bioinspired computing, deep learning

  • Hector Santos-Villalobos

    Assistant Professor, Electrical Engineering and Computer Science

    Imaging, biometrics, analytics, content understanding, NDE, dementia, AI, artificial intelligence, machine learning, computer vision, unsupervised learning, supervised learning, deep learning, human subject research

  • Catherine Schuman stands in front of a whiteboard with formulas written on it.

    Catherine Schuman

    Assistant Professor, Electrical Engineering & Computer Science

    Neuromorphic computing, smart transportation, smart infrastructure, autonomous vehicles

  • Ioannis Sgouralis

    Ioannis Sgouralis

    Assistant Professor, Mathematics

    Applied mathematics, bayesian statistics, data analysis, single molecule data, photonics, computational optics, super-resolution microscopy, spectroscopy, nucleic magnetic resonance

  • Russell Zaretzki

    Russ Zaretzki

    Associate Professor, Business Analytics and Statistics

    Applied statistics, big data analytics, computational statistics, data mining, healthcare analytics, predictive analytics

See all fundamentals of AI faculty