Xingyu Zhou | Engineering | Best Researcher Award

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Prof. Dr. Xingyu Zhou | Engineering | Best Researcher Award 

Assistant Professor | Beijing Institute of Technology | China

Dr. Zhou Xingyu, Assistant Professor at the Beijing Institute of Technology, is an accomplished researcher specializing in renewable energy and electric vehicles. He earned his Ph.D. in Vehicle Engineering from Chongqing University in 2020, following a Bachelor’s degree in Mechanical Design, Manufacturing, and Automation from the same institution. Dr. Zhou has extensive professional experience, including his current role as Assistant Professor at the School of Mechanical Engineering and Vehicle Engineering, Beijing Institute of Technology since March 2023, and a postdoctoral fellowship at the same institute from 2020 to 2023, where he contributed to the National Engineering Research Center for Electric Vehicles. His research interests focus on vehicle powertrain optimization, intelligent energy management, stochastic and data-driven modeling, and electric vehicle motion planning for enhanced energy efficiency. He has demonstrated expertise in multi-objective optimization, machine learning applications for powertrain design, and integration of fuel cell and hybrid electric vehicle systems. Dr. Zhou has led and participated in multiple high-impact research projects, including a National Natural Science Foundation of China Youth Project and key provincial and national projects on electric vehicle energy optimization and system integration. He has published 27 Scopus-indexed documents with 448 citations and an h-index of 11, in reputed journals such as Applied Energy, Journal of Power Sources, Journal of Cleaner Production, and IEEE Transactions on Vehicular Technology, serving frequently as corresponding author. His awards and honors include the Best Student Paper Award at the 2018 Italian Conference on Machines and Mechanisms. In addition, he contributes to the academic community as a reviewer for top journals and Guest Editor of Sustainability. Dr. Zhou Xingyu’s strong technical expertise, leadership in research projects, international collaborations, and commitment to sustainable innovation make him a highly deserving candidate for the Best Researcher Award, reflecting both outstanding academic achievements and meaningful contributions to advancing green mobility and energy-efficient transportation solutions globally.

Profiles: Scopus | ORCID

Featured Publications

Sun, C., Zhang, C., Sun, F., & Zhou, X. (2022). Stochastic co-optimization of speed planning and powertrain control with dynamic probabilistic constraints for safe and ecological driving. Applied Energy, 35, 119874.

Zhou, X., Sun, C., Sun, F., & Zhang, C. (2022). Commuting-pattern-oriented optimal sizing of electric vehicle powertrain based on stochastic optimization. Journal of Power Sources, 545, 23178.

Zhou, X., Sun, F., Zhang, C., & Sun, C. (2022). Stochastically predictive co-optimization of speed planning and powertrain controls for electric vehicles driving in random traffic environment safely and efficiently. Journal of Power Sources, 528, 231200.

Zhou, X., Sun, F., Sun, C., & Zhang, C. (2022). Predictive co-optimization of speed planning and powertrain energy management for electric vehicles driving in traffic scenarios: Combining strengths of simultaneous and hierarchical methods. Journal of Power Sources, 523, 230910.

Zhou, X., Sun, F., & Sun, C. (2021). Machine learning aided methods for reducing the dimensionality of the comprehensive energy economy optimization of fuel cell powertrains. Journal of Cleaner Production, 327, 129250.

Naghi Rostami | Engineering | Best Researcher Award

Published on by Best Paper Awards

Assoc. Prof. Dr. Naghi Rostami | Engineering | Best Researcher Award 

Faculty of Electrical and Computer Engineering | University of Tabriz | Iran

Dr. Naghi Rostami is an accomplished academic and researcher in electrical power engineering, currently serving as Associate Professor and Head of the Electric Power Engineering Department at the University of Tabriz, Iran, where he has held leadership responsibilities from 2018 to 2024. He completed his B.Sc. in Electrical Engineering at K. N. Toosi University of Technology in 2006, his M.Sc. at the University of Tehran in 2008, and earned his Ph.D. from the University of Tabriz in 2013. He also gained international exposure through a research opportunity at Lappeenranta University of Technology, Finland, in 2012 under the supervision of Prof. Juha Pyrhönen. His primary research interests include permanent magnet machine design, particularly axial flux and radial flux configurations, hybrid electric vehicle energy management, modeling and optimization of electrical machines, and the integration of renewable energy systems with electric vehicles and storage technologies. Dr. Rostami’s research skills span analytical and numerical design methods, genetic algorithms, particle swarm optimization, and advanced co-simulation approaches, which he has applied to the design and performance improvement of permanent magnet machines and energy systems. He has an impressive record of publications in reputable journals such as IEEE Transactions on Magnetics, IET Electric Power Applications, Sustainable Cities and Society, and COMPEL, with many works indexed in Scopus and IEEE Xplore. His Google Scholar profile records more than 1,500 citations with an H-index of 19, highlighting the international recognition of his work. While his CV does not list specific awards and honors, his achievements in leadership, international collaborations, and sustained scholarly contributions stand as testaments to his professional excellence. In conclusion, Dr. Rostami is a dedicated scholar whose expertise, impactful publications, and leadership in academia and research make him a strong candidate for recognition through distinguished awards and honors in the field of electrical power engineering.

Profiles: Google Scholar | LinkedIn | ResearchGate

Featured Publications

  1. Jalilzadeh, T., Rostami, N., Babaei, E., & Maalandish, M. (2018). Nonisolated topology for high step-up DC–DC converters. IEEE Journal of Emerging and Selected Topics in Power Electronics, 11(1), 137–150.(Cited 137 times)

  2. Rostami, N., Feyzi, M. R., Pyrhonen, J., Parviainen, A., & Niemela, M. (2012). Lumped-parameter thermal model for axial flux permanent magnet machines. IEEE Transactions on Magnetics, 49(3), 1178–1184.(Cited 136 times)

  3. Zeynali, S., Rostami, N., Ahmadian, A., & Elkamel, A. (2020). Two-stage stochastic home energy management strategy considering electric vehicle and battery energy storage system: An ANN-based scenario generation methodology. Sustainable Energy Technologies and Assessments, 39, 100722.(Cited 104 times)

  4. Marzang, V., Hosseini, S. H., Rostami, N., Alavi, P., & Mohseni, P. (2020). A high step-up nonisolated DC–DC converter with flexible voltage gain. IEEE Transactions on Power Electronics, 35(10), 10489–10500.(Cited 96 times)

  5. Zeynali, S., Rostami, N., & Feyzi, M. R. (2020). Multi-objective optimal short-term planning of renewable distributed generations and capacitor banks in power system considering uncertainties. International Journal of Electrical Power & Energy Systems, 119, 105885.(Cited 93 times)