The University of Tennessee Knoxville

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Science-Informed Artificial Intelligence

Scientist at work in the Fab Lab

Pushing the boundaries of AI in science and engineering to redefine technology

Cluster Goals

As the US government seeks to strengthen domestic manufacturing and supply chains, it is also making enormous investments in research and development to gain and sustain leadership in artificial intelligence. At the University of Tennessee, Knoxville, experts in the mathematics, sciences, and engineering disciplines of AI have joined forces to seize this unique opportunity to advance these national priorities, starting here in Tennessee. 

The vision of UT’s Science-Informed AI cluster is to lead in these areas by advancing science-informed AI in intelligent engineering systems. We will focus specifically on innovations within additive manufacturing and hypersonic defense. These systems, which align with the university’s strengths and priorities, generate multimodal, multiphysics data that challenges today’s state-of-the-art AI.

We will address the grand challenge of developing foundational multiscale, multimodal models for AI that respect the physical laws and chemical properties governing underlying processes. We’re taking up this challenge as we build a critical mass of high-caliber researchers ready to lead multi-investigator, multimillion-dollar projects—and ready to make an impact in Tennessee and beyond.

Cutting-Edge Collaboration

We’re connecting experienced leaders and rising stars from fields including: 

  • Mathematics and statistics
  • Data science and machine learning
  • Physics
  • Chemistry
  • Industrial and systems engineering
  • Mechanical and aerospace engineering
  • Computational sciences
  • Quantum computing

Ready to take the next step?

Explore Positions
Faculty member using equipment in the TN made engineering lab


Why UT?

This cluster is driving AI innovation by integrating science principles with a focus on transforming smart manufacturing and hypersonic systems—key areas that resonate with the university’s long-term vision. By advancing expertise in these high-impact fields, the cluster aims to propel UT to the forefront of innovation, creating bold opportunities for faculty to shape the future and redefine what’s possible.

Partnering with Oak Ridge National Laboratory, UT is transforming Tennessee into a hub for advanced materials and manufacturing. The cluster will leverage world-class resources at UT’s Center for Advanced Materials and Manufacturing and collaborate with the Ohio State’s Hybrid Autonomous Manufacturing, Moving from Evolution to Revolution (HAMMER) Engineering Research Center. Additionally, UT Knoxville’s cutting-edge lab upgrades, funded by the Air Force Research Laboratory, will position the university at the forefront of defense hypersonic systems research.

In tandem with the Foundational AI cluster, the cluster will enhance UT’s leadership in AI research, education, and workforce development. Collaborating with the UT –Oak Ridge Innovation Institute and the UT-led AI Tennessee Initiative, we will create a powerful framework for impactful research and innovation.

Looking forward, the cluster aims to extend its collaborations into neutron sciences, health sciences, and other fields, leveraging AI to address global challenges and solidifying UT’s role as a leader in transformative research.

Join Our Academic Community

Explore the links below to learn more about open positions. Contact the faculty lead if you don’t see an open position aligned with your skill set or if you’re a current UT faculty member who wants to get involved.

Hiring Colleges 

  • College of Arts and Sciences
  • Tickle College of Engineering

Cluster Positions

Apply Now

Assistant Professor

Focus: Large-scale optimization

Hiring Unit:

  • Department of Industrial and Systems Engineering
Apply Now

Assistant Professor

Focus: Applied scientific machine learning

Hiring Units:

  • Department of Mechanical, Aerospace, and Biomedical Engineering

Filled

Sayan Bannerjee Assistant Professor

Focus: Chemistry-informed machine learning

Hiring Unit:

  • Department of Chemistry

Filled

Ling Liang Assistant Professor

Focus: Physics-informed machine learning

Hiring Unit:

  • Department of Mathematics

Filled

Duc Nguyen Associate Professor

Focus: Geometric deep learning

Hiring Unit:

  • Department of Mathematics

Filled

Zachary Nicolaou Assistant Professor

Focus: Fundamental physics with artificial intelligence

Hiring Unit:

  • Department of Physics and Astronomy
  • Department of Mathematics

Meet Our Cluster Community

Faculty Lead

Vasileios Maroulas

Vasileios Maroulas

Professor of Mathematics, College of Arts and Sciences; Associate Vice Chancellor for Research; Director, AI Tennessee Initiative

Phone: 865-974-4302
Email: vasileios.maroulas@utk.edu

View Vasileios Maroulas’s Profile


Faculty

  • Cristian Batista.

    Cristian Batista

    Lincoln Chair Professor, Theoretical Condensed Matter Physics

    theoretical physics with emphasis in strongly interacting electron systems

  • Adrian Del Maestro

    Adrian Del Maestro

    Professor & Department Head, Physics

    quantum entanglement, quantum nanofluidics, wetting and adsorption, algorithmic development for the quantum many-body problem, quantum phase transitions

  • Thanh Do

    Thanh Do

    Assistant Professor, Chemistry

    combining ion-mobility mass spectrometry, mass spectrometry imaging, computational modeling

  • Kivanc Ekici

    Kivanc Ekici

    John W. Fisher Professor and Department Head; Mechanical, Aerospace & Biomedical Engineering

    computational fluid dynamics, wind turbine aeroelasticity, turbomachinery, fluid-structure interactions in nuclear reactors, flapping flight, rotorcraft aerodynamics

  • Rebekah Herrman

    Rebekah Herrman

    Assistant Professor, Industrial & Systems Engineering

    quantum optimization algorithms, graph theory games

  • Bradley Jared.

    Bradley Jared

    Associate Professor; Department of Mechanical, Aerospace, & Biomedical Engineering

    machine learning for manufacturing processes

  • Sergei Kalinin.

    Sergei Kalinin

    Weston Fulton Professor, Materials Science & Engineering

    applications of machine learning and artificial intelligence for physics extraction from the atomically-resolved and mesoscopic imaging data

  • Anahita Khojandi

    Anahita Khojandi

    Associate Professor, Industrial & Systems Engineering

    Markov decision processes, dynamic programming, predictive analytics, reinforcement learning, time series analysis, anomaly detection

  • Duc Nguyen.

    Duc Nguyen

    Associate Professor, Mathematics

    advanced machine learning, deep learning methods for drug design

  • james ostrowski

    James Ostrowski

    Dan Doulet Faculty Fellow, Professor, Associate Department Head, & Director of Graduate Studies; Industrial & Systems Engineering

    integer programming, stochastic programming, non-linear programming, combinatorial optimization, power systems, scheduling problems, energy markets

  • A computer illustration of an outline of a person wearing a UT lab coat with orange accents.

    Omer San

    Associate Professor; Mechanical, Aerospace, & Biomedical Engineering

    scientific machine learning, digital twins, artificial intelligence, data assimilation, high performance computing, fluid dynamics and turbulence

  • John Schmisseur.

    John Schmisseur

    Executive Director, UT Space Institute

    hypersonics, aerospace engineering, defense capabilities

  • Tony Schmitz.

    Tony Schmitz

    Professor; Mechanical, Aerospace, & Biomedical Engineering

    manufacturing, machining, vibrations, measurement, uncertainty analysis

  • Ioannis Sgouralis.

    Ioannis Sgouralis

    Assistant Professor, Mathematics

    data modeling and interpretation, bayesian nonparametrics, computational statistics, biomedicine, single molecule biophysics/biochemistry

  • Alan Tennant.

    David Alan Tennant

    Professor, Experimental Condensed Matter Physics

    exploring quantum magnetic phenomena using neutron scattering

  • Konstantinos Vogiatzis

    Konstantinos Vogiatzis

    Associate Professor, Chemistry

    computational methods based on electronic structure theory and artificial intelligence for describing chemical systems relevant to clean, green technologies

  • Bing Yao.

    Bing Yao

    Dan Doulet Early Career Assistant Professor, Industrial & Systems Engineering

    developing innovative physical-statistical models for decision optimization in complex systems


Cluster Hiring Initiatives

The University of Tennessee, Knoxville, has committed $50 million over five years to recruit top-tier faculty members across multiple disciplines.

Our faculty community is a critical driver of progress toward realizing UT’s ambitious Strategic Vision. The cluster hiring process enables faculty-led excellence in transdisciplinary research and teaching through a significant commitment of institutional resources.

The University of Tennessee, Knoxville
Knoxville, Tennessee 37996
865-974-1000

The flagship campus of the University of Tennessee System and partner in the Tennessee Transfer Pathway.

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