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Researcher
- Amit Shyam
- Alex Plotkowski
- Sam Hollifield
- Srikanth Yoginath
- Chad Steed
- James A Haynes
- James J Nutaro
- Junghoon Chae
- Mingyan Li
- Peeyush Nandwana
- Pratishtha Shukla
- Rangasayee Kannan
- Ryan Dehoff
- Sudip Seal
- Sumit Bahl
- Travis Humble
- Aaron Werth
- Adam Stevens
- Alice Perrin
- Ali Passian
- Andres Marquez Rossy
- Brian Post
- Brian Weber
- Bryan Lim
- Christopher Fancher
- Dean T Pierce
- Emilio Piesciorovsky
- Gary Hahn
- Gerry Knapp
- Gordon Robertson
- Harper Jordan
- Isaac Sikkema
- Jason Jarnagin
- Jay Reynolds
- Jeff Brookins
- Joel Asiamah
- Joel Dawson
- Joseph Olatt
- Jovid Rakhmonov
- Kevin Spakes
- Kunal Mondal
- Lilian V Swann
- Luke Koch
- Mahim Mathur
- Mark Provo II
- Mary A Adkisson
- Nance Ericson
- Nicholas Richter
- Oscar Martinez
- Pablo Moriano Salazar
- Peter Wang
- Raymond Borges Hink
- Rob Root
- Roger G Miller
- Samudra Dasgupta
- Sarah Graham
- Sudarsanam Babu
- Sunyong Kwon
- T Oesch
- Tomas Grejtak
- Varisara Tansakul
- William Peter
- Yarom Polsky
- Ying Yang
- Yiyu Wang
- Yukinori Yamamoto

Currently available cast Al alloys are not suitable for various high-performance conductor applications, such as rotor, inverter, windings, busbar, heat exchangers/sinks, etc.

The ever-changing cellular communication landscape makes it difficult to identify, map, and localize commercial and private cellular base stations (PCBS).

The invented alloys are a new family of Al-Mg alloys. This new family of Al-based alloys demonstrate an excellent ductility (10 ± 2 % elongation) despite the high content of impurities commonly observed in recycled aluminum.

The lack of real-time insights into how materials evolve during laser powder bed fusion has limited the adoption by inhibiting part qualification. The developed approach provides key data needed to fabricate born qualified parts.

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.

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.