Junpeng Zhan

Junpeng Zhan is an Assistant Professor of Renewable Energy Engineering at the Inamori School of Engineering, Alfred University, NY, USA. He holds a Ph.D. and B.Sc. in Electrical Engineering from Zhejiang University (2014 and 2009). Before joining Alfred, he worked as a Research Associate at Brookhaven National Laboratory (2018–2020), a Postdoctoral Fellow at the University of Saskatchewan and Hong Kong Polytechnic University, and a Visiting Research Assistant at the University of Liverpool.

His research focuses on quantum computing, optimization methods, smart grid technologies, machine learning, and renewable energy integration. Notable contributions include developing the Quantum Feasibility Labeling algorithm and the hybrid Variational Quantum Search, which address NP-complete problems like the Vertex Coloring problem. He currently leads NSF-funded projects on variational quantum algorithms for power system simulation and ISO-New England-funded work on quantum computing for unit commitment.

Zhan is an Associate Editor of IET Generation, Transmission & Distribution and actively reviews for 20+ journals. His grants include $199,980 from the NSF (2022), $50,000 from ISO-New England (2024–2026), and a co-PI role in a $1.37M NYSERDA-funded workforce training initiative. His work bridges fundamental research and practical energy system challenges, emphasizing computational innovation and scalability.

Labs and collaborations include the Engineering Laboratories at Alfred University, with partnerships extending to institutions like RIT and GE. His teaching spans courses in power systems, Python for research, and mechatronics.