{"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":"2026-04-14T16:08:42","modified_gmt":"2026-04-14T20:08:42","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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Kalinin\u2019s AI Microscopist Accelerates Nanoscale Material Characterization<\/a><\/h3>\n\n\n\n

With support from the\u202fUS Department of Energy, Sergei Kalinin\u2019s team launched a new AI-enabled workflow integrating machine learning, high-performance computing, and advanced microscopy. The workflow can gather useful data up to 100 times faster than conventional methods. 

Learn more about this research.<\/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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Wang Investigates Autonomous Vehicle Control for Advanced Air Mobility Systems<\/a><\/h3>\n\n\n\n

Zhenbo Wang\u2019s lab is developing and testing a novel airway system coupled with adaptive operational rules and control schemes. They are devising algorithms to facilitate autonomous control, adaptability, and optimal decision-making based on real-time factors.  

Learn about Wang’s vision for air mobility systems.<\/a><\/p>\n<\/div>\n<\/div>\n<\/div>\n\n\n\n

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Group Combines High Performance Computing and AI to Advance Data Sciences<\/a><\/h3>\n\n\n\n

With a multiple-year award from the National Science Foundation, Michela Taufer is leading research to make developing tailored neural networks faster and more efficient. Improving neural networks in these ways will drive greater efficiency in diverse AI systems with data-based decision-making at their core.

Learn more about this research.<\/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