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Researcher
- Vivek Sujan
- Amit Shyam
- Beth L Armstrong
- Peeyush Nandwana
- Alex Plotkowski
- Brian Post
- Jun Qu
- Omer Onar
- Rangasayee Kannan
- Sudarsanam Babu
- Yong Chae Lim
- Adam Siekmann
- Blane Fillingim
- Corson Cramer
- Erdem Asa
- James A Haynes
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- Meghan Lamm
- Ryan Dehoff
- Shajjad Chowdhury
- Steve Bullock
- Subho Mukherjee
- Sumit Bahl
- Thomas Feldhausen
- Tomas Grejtak
- Ying Yang
- Yousub Lee
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- Bruce A Pint
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- Christopher Ledford
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- Dean T Pierce
- Ethan Self
- Gabriel Veith
- Gerry Knapp
- Glenn R Romanoski
- Gordon Robertson
- Govindarajan Muralidharan
- Hyeonsup Lim
- Isabelle Snyder
- James Klett
- Jay Reynolds
- Jeff Brookins
- Jiheon Jun
- Jordan Wright
- Jovid Rakhmonov
- Khryslyn G Araño
- Marm Dixit
- Matthew S Chambers
- Michael Kirka
- Nancy Dudney
- Nicholas Richter
- Peter Wang
- Priyanshi Agrawal
- Roger G Miller
- Rose Montgomery
- Sarah Graham
- Sergiy Kalnaus
- Steven J Zinkle
- Sunyong Kwon
- Thomas R Muth
- Tim Graening Seibert
- Tolga Aytug
- Trevor Aguirre
- Venugopal K Varma
- Weicheng Zhong
- Wei Tang
- William Peter
- Xiang Chen
- Yanli Wang
- Yiyu Wang
- Yukinori Yamamoto
- Yutai Kato
- Zhili Feng

Mechanism-Based Biological Inference via Multiplex Networks, AI Agents and Cross-Species Translation
This invention provides a platform that uses AI agents and biological networks to uncover and interpret disease-relevant biological mechanisms.

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.

The growing demand for electric vehicles (EVs) has necessitated significant advancements in EV charging technologies to ensure efficient and reliable operation.

The growing demand for renewable energy sources has propelled the development of advanced power conversion systems, particularly in applications involving fuel cells.

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.

This invention presents a multiport converter (MPC) based power supply to charge the 12 V and 24 V auxiliary batteries in heavy duty (HD) fuel cell (FC) electric vehicle (EV) power train.