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Researcher
- Alex Plotkowski
- Amit Shyam
- Srikanth Yoginath
- Chad Steed
- James A Haynes
- James J Nutaro
- Junghoon Chae
- Peeyush Nandwana
- Pratishtha Shukla
- Sudip Seal
- Sumit Bahl
- Travis Humble
- Alice Perrin
- Ali Passian
- Andres Marquez Rossy
- Bryan Lim
- Debangshu Mukherjee
- Gerry Knapp
- Harper Jordan
- Joel Asiamah
- Joel Dawson
- Jovid Rakhmonov
- Md Inzamam Ul Haque
- Nance Ericson
- Nicholas Richter
- Olga S Ovchinnikova
- Pablo Moriano Salazar
- Rangasayee Kannan
- Ryan Dehoff
- Samudra Dasgupta
- Sunyong Kwon
- Tomas Grejtak
- Varisara Tansakul
- Ying Yang
- Yiyu Wang

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 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.

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.

This innovative approach combines optical and spectral imaging data via machine learning to accurately predict cancer labels directly from tissue images.