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Researcher
- Vivek Sujan
- Adam Siekmann
- Anees Alnajjar
- Omer Onar
- Subho Mukherjee
- Yong Chae Lim
- Zhili Feng
- Erdem Asa
- Isabelle Snyder
- Jian Chen
- Nageswara Rao
- Rangasayee Kannan
- Wei Zhang
- Adam Stevens
- Brian Post
- Bryan Lim
- Craig A Bridges
- Dali Wang
- Hyeonsup Lim
- Jiheon Jun
- Mariam Kiran
- Peeyush Nandwana
- Priyanshi Agrawal
- Roger G Miller
- Ryan Dehoff
- Sarah Graham
- Shajjad Chowdhury
- Sheng Dai
- Sudarsanam Babu
- Tomas Grejtak
- William Peter
- Yiyu Wang
- Yukinori Yamamoto

The eDICEML digital twin is proposed which emulates networks and hosts of an instrument-computing ecosystem. It runs natively on an ecosystem’s host or as a portable virtual machine.

Here we present a solution for practically demonstrating path-aware routing and visualizing a self-driving network.

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.

This invention is directed to a machine leaning methodology to quantify the association of a set of input variables to a set of output variables, specifically for the one-to-many scenarios in which the output exhibits a range of variations under the same replicated input condi

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.

Electrochemistry synthesis and characterization testing typically occurs manually at a research facility.