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Researcher
- Vivek Sujan
- Omer Onar
- Adam Siekmann
- Ali Riza Ekti
- Chad Steed
- Erdem Asa
- Isabelle Snyder
- Junghoon Chae
- Mingyan Li
- Raymond Borges Hink
- Sam Hollifield
- Subho Mukherjee
- Travis Humble
- Aaron Werth
- Aaron Wilson
- Brian Weber
- Burak Ozpineci
- Elizabeth Piersall
- Emilio Piesciorovsky
- Emrullah Aydin
- Gary Hahn
- Hyeonsup Lim
- Isaac Sikkema
- Joseph Olatt
- Kevin Spakes
- Kunal Mondal
- Lilian V Swann
- Luke Koch
- Mahim Mathur
- Mary A Adkisson
- Mostak Mohammad
- Nils Stenvig
- Oscar Martinez
- Ozgur Alaca
- Peter L Fuhr
- Samudra Dasgupta
- Shajjad Chowdhury
- T Oesch
- Yarom Polsky

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 technology can help to increase number of application areas of Wireless Power Transfer systems. It can be applied to consumer electronics, defense industry, automotive industry etc.

Faults in the power grid cause many problems that can result in catastrophic failures. Real-time fault detection in the power grid system is crucial to sustain the power systems' reliability, stability, and quality.

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.

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.

This invention presents an integrated strategy to reduce end-user electricity costs and grid carbon emissions by efficiently utilizing Distributed Energy Resources (DER) and grid-scale electrical energy storage systems, such as batteries.

No readily available public data exists for vehicle class and weight information that covers the entire U.S. highway network. The Travel Monitoring Analysis System, managed by the Federal Highway Administration covers only less than 1% of the US highway network.