{"id":351,"date":"2023-01-13T12:31:52","date_gmt":"2023-01-13T17:31:52","guid":{"rendered":"https:\/\/research-multi-dev.utk.edu\/energy-dev\/?page_id=351"},"modified":"2026-06-26T14:56:28","modified_gmt":"2026-06-26T18:56:28","slug":"ai-systems","status":"publish","type":"page","link":"https:\/\/research.utk.edu\/aitn\/research-areas\/ai-systems\/","title":{"rendered":"AI Systems"},"content":{"rendered":"\n
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AI Systems<\/h1>\n\n\n\n

Bridging AI and real-world challenges to drive efficiency and opportunity<\/em> <\/em><\/p>\n<\/div>

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UT researchers in AI systems form the bridge between the fundamentals<\/a> of AI\u2014such as the computing architectures, statistical models, and algorithms that undergird machine learning\u2014and positive outcomes for science, industry, and humanity.<\/p>\n\n\n\n

Faculty design and build intelligent systems by coordinating the interactions between distinct AI elements such as machine learning pipelines, autonomous agents, edge AI, and AI-driven simulations. Researchers continue to optimize these systems for accuracy, efficiency, flexibility, and scalability, allowing them to transform workflows, enable process efficiency, and shape decision-making in applications<\/a> from astronomy to zoology.<\/p>\n<\/div>\n\n\n\n

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UT’s Approach<\/h2>\n\n\n\n

UT researchers are integrating AI, machine learning, high-performance computing, and cloud platforms to tackle challenges in large-scale data distribution, storage, and computation, making AI workflows faster, more efficient, and more trustworthy. They are advancing autonomous systems across domains\u2014from globally connected microscopy networks to air mobility to autonomous driving models that improve safety and reduce congestion. In agriculture, faculty combine computer vision, Internet of Things devices, and deep learning to strengthen food security with farm-specific digital twins, robotic pest monitoring, and automated pollination systems. In health and human services, they are developing socially assistive robots for dementia care, AI-enabled surgical systems, and diagnostic tools for conditions like atrial fibrillation. By uniting machine learning frameworks, physical mechanisms, and control systems, UT is creating intelligent robots capable of operating in unstructured environments, expanding the reach of AI into discovery, mobility, agriculture, and health care.<\/p>\n<\/div>\n\n\n\n

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UT has moved quickly and early in the emerging high-potential field of fully automated materials synthesis. The university has invested in our work building AI-enabled systems and workflows. With these unique operational capabilities, UT can truly make an impact on the state, country, and world.\u201d<\/h2>\n\n\n\n
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Sergei Kalinin, Weston Fulton Professor of Materials Science and Engineering, UT; Chief Scientist, AI\/ML for Physical Sciences, Pacific Northwest National Laboratory<\/em><\/p>\n<\/blockquote>\n<\/div>\n<\/div>\n\n\n\n

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Highlights <\/h2>\n\n\n\n
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Suya and Cisco Join Forces for Cybersecurity<\/a><\/h3>\n\n\n\n

Supported by an AI TechX seed grant, Fnu Suya is working with Cisco to investigate how custom hardware vulnerabilities might interact with various types of AI models. This collaboration between academia and industry will provide insight for translating scientific results into usable cybersecurity tools.\u00a0

Learn more about the collaboration.<\/a><\/p>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n

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Surgical Robot Project Receives Up to $12 Million in ARPA-H Funding<\/a><\/h3>\n\n\n\n

Caleb Rucker is co-principal investigator in a multi-institutional project to create a surgical robot capable of performing an entire surgery without human intervention. Rucker is leading a UT team in developing computational models to inform the automated surgery system. 

Learn about this landmark project.<\/a><\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n

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Xing\u2019s Research Uses AI to Improve Weather, Air Quality Forecasting<\/a><\/h3>\n\n\n\n

Jia Xing\u2019s latest research is advancing the ability to predict weather and air quality by using AI and geoscience to create a new generation of forecasting tools that are faster, more accurate, and more responsive than current numerical model\u2013based systems.\u00a0

Learn more about Xing\u2019s funded projects.<\/a><\/p>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n

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Cao\u2019s Digital Twin Expertise Helps Global Farmers<\/a><\/h3>\n\n\n\n

Charles Cao is spearheading development of an AI-driven digital twin, building an integrated system that connects AI and engineering expertise with real-world agricultural research. Funded through the National Institutes of Health, the project is part of an international effort to create next-generation tools that can help farmers identify and manage agricultural threats.

Learn more about the project.<\/a><\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n

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Facilities & Initiatives<\/h2>\n\n\n\n
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Faculty study and build AI systems in state-of-the-art facilities on and off campus. Centers and research groups receive support from and partner with organizations including the National Science Foundation, the US Department of Energy, the US Department of Transportation, and industry leaders.  <\/p>\n\n\n\n