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Researcher
- Vivek Sujan
- Omer Onar
- Srikanth Yoginath
- Adam Siekmann
- Erdem Asa
- James J Nutaro
- Pratishtha Shukla
- Subho Mukherjee
- Sudip Seal
- Alex Roschli
- Ali Passian
- Bryan Lim
- Erin Webb
- Evin Carter
- Harper Jordan
- Hyeonsup Lim
- Isabelle Snyder
- Jeremy Malmstead
- Joel Asiamah
- Joel Dawson
- Kitty K Mccracken
- Mengdawn Cheng
- Nance Ericson
- Oluwafemi Oyedeji
- Pablo Moriano Salazar
- Paula Cable-Dunlap
- Peeyush Nandwana
- Rangasayee Kannan
- Shajjad Chowdhury
- Soydan Ozcan
- Tomas Grejtak
- Tyler Smith
- Varisara Tansakul
- Xianhui Zhao
- 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.

The use of biomass fiber reinforcement for polymer composite applications, like those in buildings or automotive, has expanded rapidly due to the low cost, high stiffness, and inherent renewability of these materials. Biomass are commonly disposed of as waste.

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.

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.