Foundational Artificial intelligence

Cluster Goals

The potential benefits of artificial intelligence continue to unfold for corporate, government, and institutional applications. Despite rapid advancements in deep learning, however, the gap between artificial and human intelligence is far from closed. Major funding agencies are prioritizing foundational AI research to change that.

The Foundational AI cluster at the University of Tennessee, Knoxville, is pursuing a once-in-a-generation opportunity to profoundly shape and accelerate AI development. Our vision is to build UT’s leadership position by focusing on dynamic learning in the early developmental stage of human intelligence and developing AI solutions inspired by cognitive neuroscience.

We’re deepening our foundational understanding of how human infants learn as they interact with their surroundings and applying the insights we gain to advance embodied learning in AI. We aim to apply our foundational findings to robotic learning in embodied environments and to implementation in edge devices. We envision how our work could improve applications such as surgical and social robots. Together we’ll enable AI to make life and lives better in new ways.

Intelligently Interdisciplinary

We’re bringing researchers together from fields across UT, including:

• Psychology and neuroscience
• Computer science
• Computer engineering
• Computational and applied mathematics
• Biomedical engineering

Why UT?

Joining UT’s Foundational AI cluster means advancing a shared vision, interfacing directly with colleagues on shared proposals and publications, and tapping into the university’s broader AI research community to expand your opportunities. 

The cluster is specifically concerned with closing the gap between AI and early developmental learning. This focus distinguishes it from initiatives at other universities and concentrates our efforts. The UT Department of Psychology’s unique strengths in child development research, including six specialized labs, will undergird ongoing work across disciplines as we investigate dynamic learning from developmental, functional, mathematical, and implementation perspectives. 

We’ll collaborate with the AI Tennessee Initiative, a UT-led partnership bringing AI’s benefits to manufacturing, mobility, agriculture, and other economic sectors. Former AI Tennessee Director Lynne Parker, whose wealth of experience includes leading federal AI policy efforts, will join other eminent experts in advising our cluster. UT is also investing in a science-informed AI cluster, which will enable us to cross-fertilize ideas and investigate how our insights can be translated into more applications with real-world impacts.

We will expand opportunities in AI for our students, too. We will collaborate with existing programs, such as the Bredesen Center for Interdisciplinary Research and Graduate Education Data Science and Engineering (DSE) PhD program, and build robust new curricula. Over time, new cluster hires will lead the development of interdisciplinary courses, a graduate certificate, and an undergraduate minor to prepare students for cutting-edge careers.