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Researcher
- Vivek Sujan
- Omer Onar
- Srikanth Yoginath
- Adam Siekmann
- Erdem Asa
- James J Nutaro
- Pratishtha Shukla
- Subho Mukherjee
- Sudip Seal
- Ali Passian
- Bryan Lim
- Gerald Tuskan
- Harper Jordan
- Hyeonsup Lim
- Ilenne Del Valle Kessra
- Isabelle Snyder
- Joel Asiamah
- Joel Dawson
- Nance Ericson
- Pablo Moriano Salazar
- Paul Abraham
- Peeyush Nandwana
- Rangasayee Kannan
- Shajjad Chowdhury
- Tomas Grejtak
- Varisara Tansakul
- Vilmos Kertesz
- Xiaohan Yang
- Yang Liu
- 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.

Detection of gene expression in plants is critical for understanding the molecular basis of plant physiology and plant responses to drought, stress, climate change, microbes, insects and other factors.

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.