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Researcher
- Vivek Sujan
- Omer Onar
- Srikanth Yoginath
- Adam Siekmann
- Andrzej Nycz
- Chad Steed
- Erdem Asa
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- Junghoon Chae
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- Sudip Seal
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- Clay Leach
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- Peeyush Nandwana
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- Samudra Dasgupta
- Shajjad Chowdhury
- Tomas Grejtak
- Varisara Tansakul
- Vincent Paquit
- Xiaohan Yang
- Yiyu Wang

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.

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.

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

QVis is a visual analytics tool that helps uncover temporal and multivariate variations in noise properties of quantum devices.

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.