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Researcher
- Srikanth Yoginath
- Alex Roschli
- Chad Steed
- James J Nutaro
- Junghoon Chae
- Pratishtha Shukla
- Sudip Seal
- Travis Humble
- Ali Passian
- Annetta Burger
- Brian Post
- Bryan Lim
- Cameron Adkins
- Carter Christopher
- Chance C Brown
- Debraj De
- Diana E Hun
- Erin Webb
- Evin Carter
- Gautam Malviya Thakur
- Gina Accawi
- Gurneesh Jatana
- Harper Jordan
- Isha Bhandari
- James Gaboardi
- Jeremy Malmstead
- Jesse McGaha
- Joel Asiamah
- Joel Dawson
- Kevin Sparks
- Kitty K Mccracken
- Liam White
- Liz McBride
- Mark M Root
- Mengdawn Cheng
- Michael Borish
- Nance Ericson
- Oluwafemi Oyedeji
- Pablo Moriano Salazar
- Paula Cable-Dunlap
- Peeyush Nandwana
- Philip Boudreaux
- Rangasayee Kannan
- Samudra Dasgupta
- Soydan Ozcan
- Todd Thomas
- Tomas Grejtak
- Tyler Smith
- Varisara Tansakul
- Venkatakrishnan Singanallur Vaidyanathan
- Xianhui Zhao
- Xiuling Nie
- Yiyu Wang

Often there are major challenges in developing diverse and complex human mobility metrics systematically and quickly.

We have been working to adapt background oriented schlieren (BOS) imaging to directly visualize building leakage, which is fast and easy.

A new nanostructured bainitic steel with accelerated kinetics for bainite formation at 200 C was designed using a coupled CALPHAD, machine learning, and data mining approach.

The use of biomass fiber reinforcement for polymer composite applications, like those in buildings or automotive, has expanded rapidly due to the low cost, high stiffness, and inherent renewability of these materials. Biomass are commonly disposed of as waste.

Digital twins (DTs) have emerged as essential tools for monitoring, predicting, and optimizing physical systems by using real-time data.

Simulation cloning is a technique in which dynamically cloned simulations’ state spaces differ from their parent simulation due to intervening events.

The QVis Quantum Device Circuit Optimization Module gives users the ability to map a circuit to a specific quantum devices based on the device specifications.

QVis is a visual analytics tool that helps uncover temporal and multivariate variations in noise properties of quantum devices.

We have developed an aerosol sampling technique to enable collection of trace materials such as actinides in the atmosphere.