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Researcher
- Amit Shyam
- Beth L Armstrong
- Peeyush Nandwana
- Alex Plotkowski
- Brian Post
- Jun Qu
- Rangasayee Kannan
- Sudarsanam Babu
- Yong Chae Lim
- Andrzej Nycz
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- Zhili Feng
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- Debraj De
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- Eve Tsybina
- Gabriel Veith
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- Gordon Robertson
- Govindarajan Muralidharan
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- James Klett
- Jay Reynolds
- Jeff Brookins
- Jesse McGaha
- Jessica Moehl
- Jian Chen
- Jiheon Jun
- Jordan Wright
- Jovid Rakhmonov
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- Khryslyn G Araño
- Liz McBride
- Marm Dixit
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- Michael Kirka
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- Nicholas Richter
- Peter Wang
- Philipe Ambrozio Dias
- Priyanshi Agrawal
- Roger G Miller
- Rose Montgomery
- Sarah Graham
- Sergiy Kalnaus
- Shajjad Chowdhury
- Steven J Zinkle
- Sunyong Kwon
- Taylor Hauser
- Thomas R Muth
- Tim Graening Seibert
- Todd Thomas
- Tolga Aytug
- Trevor Aguirre
- Venugopal K Varma
- Vincent Paquit
- Weicheng Zhong
- Wei Tang
- Wei Zhang
- William Peter
- Xiang Chen
- Xiaohan Yang
- Xiuling Nie
- Yanli Wang
- Yiyu Wang
- Yukinori Yamamoto
- Yutai Kato

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

A finite element approach integrated with a novel constitute model to predict phase change, residual stresses and part deformation.

Understanding building height is imperative to the overall study of energy efficiency, population distribution, urban morphologies, emergency response, among others. Currently, existing approaches for modelling building height at scale are hindered by two pervasive issues.

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 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.

We present the design, assembly and demonstration of functionality for a new custom integrated robotics-based automated soil sampling technology as part of a larger vision for future edge computing- and AI- enabled bioenergy field monitoring and management technologies called

Water heaters and heating, ventilation, and air conditioning (HVAC) systems collectively consume about 58% of home energy use.