Jingyuan Zhao | Energy and Sustainability | Research Excellence Award

Dr. Jingyuan Zhao | Energy and Sustainability | Research Excellence Award

University of California Davis | United States

Jingyuan (Andy) Zhao, Ph.D., is an Assistant Professional Researcher and independent principal investigator at the University of California, Davis, internationally recognized for pioneering work in AI-enabled battery and energy systems. His research integrates multiphysics and multiscale modeling with advanced artificial intelligence to address battery safety, diagnostics, prognostics, and system-level optimization for electrified transportation.  He has led or co-led major U.S. and international research projects supported by USDOT, Caltrans, CEC, CARB, and national science foundations in China, while also translating research into industrial impact through prior leadership roles in electric vehicle battery intelligence. His academic training spans mechanical and vehicle engineering, complemented by extensive postdoctoral research in the U.S. and China. Dr. Zhao has received numerous honors, including Elsevier–Stanford World’s Top 2% Scientist and ScholarGPS Top 0.5% Scholar distinctions. Through interdisciplinary scholarship, global collaboration, and mentorship, his work advances safe, intelligent, and scalable battery energy systems, bridging laboratory innovation with real-world deployment and shaping the future of sustainable mobility.

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Featured Publications


Review on Supercapacitors: Technologies and Performance Evaluation
J. Zhao, A.F. Burke, Journal of Energy Chemistry, 59, 276–291, 2021. (Citations: 602)


Autonomous Driving System: A Comprehensive Survey
J. Zhao, W. Zhao, B. Deng, Z. Wang, F. Zhang, et al., Expert Systems with Applications, 242, 122836, 2024. (Citations: 330)


Electrochemical Capacitors: Materials, Technologies and Performance
J. Zhao, A.F. Burke, Energy Storage Materials, 36, 31–55, 2021. (Citations: 202)


Electrochemical Capacitors: Performance Metrics and Evaluation by Testing and Analysis
J. Zhao, A.F. Burke, Advanced Energy Materials, 11(1), 2002192, 2021. (Citations: 182)


Machine Learning for Predicting Battery Capacity for Electric Vehicles
J. Zhao, H. Ling, J. Liu, J. Wang, A.F. Burke, Y. Lian, eTransportation, 15, 100214, 2023. (Citations: 171)

Kamal Reddad | Advanced Materials Engineering | Research Excellence Award

Mr. Kamal Reddad | Advanced Materials Engineering | Research Excellence Award

Ibn Tofail University Kenitra | Morocco

Kamal Reddad is a doctoral researcher in computational materials science specializing in hydrogen storage materials for sustainable energy applications. He is currently pursuing a PhD at the National School of Applied Sciences (ENSA), Ibn Tofail University, with a strong academic background in physics, holding a master’s degree in matter and radiation and a bachelor’s degree in physics with a focus on energetics. His research centers on magnesium hydride (MgH₂), where he investigates hydrogen desorption mechanisms using density functional theory (DFT), predictive temperature programmed desorption (TPD) modeling, and kinetic Monte Carlo (KMC) simulations. His work emphasizes the role of transition-metal doping and vacancy defects in enhancing hydrogen release kinetics, contributing to multiscale frameworks that bridge atomistic insights with macroscopic behavior. He has authored several peer-reviewed journal articles in high-impact Q1 and Q2 journals and actively contributes to the scientific community as a peer reviewer.  In recognition of academic excellence, he received the UM5 Excellence Prize during his master’s studies. Overall, his research aims to advance first-principles-driven materials design for next-generation hydrogen storage technologies and clean energy systems.

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Enhancing Hydrogen Desorption in MgH2: A DFT Study on the Effects of Copper and Zinc Doping
K. Reddad, H. Labrim, D. Zejli, R. El Bouayadi.
International Journal of Hydrogen Energy, 2024, 87, 1474–1479. (Citations: 26)


Predictive Modeling of Temperature Programmed Desorption (TPD) in Magnesium Hydride MgH2
K. Reddad, H. Labrim, R. El Bouayadi.
Fuel, 2026, 403, 136152. (Citations: 5)


Vacancy Defects and Mo Doping Synergy in MgH2: A DFT Study on Hydrogen Desorption and Electronic Enhancement
K. Reddad, H. Labrim, R. El Bouayadi.
International Journal of Hydrogen Energy, 2025, 157, 150454. (Citations: 5)


Kinetic Monte Carlo Simulations of Hydrogen Desorption: The Influence of Rhodium in MgH2
K. Reddad, H. Labrim, R. El Bouayadi.
Bulletin of Materials Science, 2026, 49(1), 7. (Accepted)