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Researcher
- Vivek Sujan
- Andrzej Nycz
- Chris Masuo
- Peter Wang
- Adam Siekmann
- Alex Walters
- Omer Onar
- Subho Mukherjee
- Yong Chae Lim
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- Isabelle Snyder
- Joshua Vaughan
- Luke Meyer
- Rangasayee Kannan
- Udaya C Kalluri
- William Carter
- Zhili Feng
- Adam Stevens
- Akash Jag Prasad
- Amit Shyam
- Bryan Lim
- Calen Kimmell
- Chelo Chavez
- Christopher Fancher
- Chris Tyler
- Clay Leach
- Gordon Robertson
- Hyeonsup Lim
- J.R. R Matheson
- Jaydeep Karandikar
- Jay Reynolds
- Jeff Brookins
- Jesse Heineman
- Jian Chen
- Jiheon Jun
- John Potter
- Peeyush Nandwana
- Priyanshi Agrawal
- Riley Wallace
- Ritin Mathews
- Roger G Miller
- Ryan Dehoff
- Sarah Graham
- Shajjad Chowdhury
- Sudarsanam Babu
- Tomas Grejtak
- Vincent Paquit
- Vladimir Orlyanchik
- Wei Zhang
- William Peter
- Xiaohan Yang
- Yiyu Wang
- Yukinori Yamamoto

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

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.

System and method for part porosity monitoring of additively manufactured components using machining
In additive manufacturing, choice of process parameters for a given material and geometry can result in porosities in the build volume, which can result in scrap.

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

Creating a framework (method) for bots (agents) to autonomously, in real time, dynamically divide and execute a complex manufacturing (or any suitable) task in a collaborative, parallel-sequential way without required human interaction.

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.