- Professor at Northwestern Polytechnical University, China
Zhanjun Huang is a highly accomplished researcher in the field of electrical engineering, specializing in power electronics, machine learning, and artificial intelligence. With a strong academic background and extensive experience in both academia and industry, he has made significant contributions to fault diagnosis and health management systems for various electromechanical systems. Zhanjun has a proven track record of publishing in top-tier journals and conferences and has received numerous awards and honors for his research work. He is an active member of several professional societies and serves as a reviewer for prominent international journals in his field.
Author Metrics
Zhanjun Huang’s research output is characterized by high-quality publications and strong author metrics. His work has been cited extensively, demonstrating its influence and relevance within the academic community. With a focus on impactful research and dissemination of knowledge, Zhanjun consistently strives for excellence in both scholarly output and author reputation.
Scopus Link
Citations: 517 citations by 448 documents
Documents: 21
h-index: 11
Education
Zhanjun Huang holds a Ph.D. in Power Electronics and Power Transmission from Northeast University, where he also completed his master’s and bachelor’s degrees in Electrical Theory and New Technology and Communication Engineering, respectively. His educational background has provided him with a solid foundation in electrical engineering principles and advanced knowledge in machine learning, data processing, and fault diagnosis.
Research Focus
Zhanjun Huang’s research focuses on several key areas, including machine learning, artificial intelligence, pattern recognition, and their applications in fault diagnosis and health management systems. His work encompasses a wide range of electromechanical systems, avionics, data links, and network communication. He is also actively involved in research related to Model-Based Systems Engineering (MBSE), Digital Twin technology, and Digital Transformation strategies, aiming to enhance the performance and reliability of complex systems.
Professional Journey
Throughout his professional journey, Zhanjun Huang has been actively engaged in both academic research and industry collaborations. He has undertaken or participated in numerous projects funded by prestigious organizations such as the National Natural Science Foundation of China, Beijing Special Machinery, and AVIC Xifei. His expertise and contributions have been recognized through appointments to the Shaanxi Provincial Talent Plan and receipt of awards such as the Excellent Doctoral Dissertation and Huawei Scholarship.
Honors & Awards
Zhanjun Huang’s dedication to research excellence has been acknowledged through various honors and awards. He has been recognized for his outstanding doctoral dissertation and has received scholarships from industry leaders like Huawei. Additionally, his research contributions have been rewarded with selection for the Shaanxi Provincial Talent Plan and other prestigious accolades, highlighting his significant impact in the field of electrical engineering.
Publications Top Noted & Contributions
Zhanjun Huang has authored and co-authored more than 30 papers and patents, many of which have been published in high-impact journals and presented at leading conferences. His research contributions span a wide range of topics, including fault diagnosis algorithms for microgrid inverters, adaptive control for MIMO systems, and distributed fault detection for nonlinear multi-agent systems. These publications reflect his innovative approaches and expertise in applying advanced techniques to solve complex engineering problems.
Title: Multi-UAV task allocation based on GCN-inspired binary stochastic L-BFGS
Authors: Zhang, A.; Zhang, B.; Bi, W.; Huang, Z.; Yang, M.
Journal: Computer Communications
Year: 2023
Volume: 212
Pages: 198–211
Title: Asymmetric Calibration and Characterization for Diff-Port Magnetic Field Probing System
Authors: Shao, W.; Li, H.; Huang, Z.; [and others]
Journal: IEEE Sensors Journal
Year: 2023
Volume: 23
Issue: 10
Pages: 10559–10567
Citations: 3
Title: Complementary Virtual Mirror Fault Diagnosis Method for Microgrid Inverter
Authors: Huang, Z.; Wang, Z.; Song, C.
Journal: IEEE Transactions on Industrial Informatics
Year: 2021
Volume: 17
Issue: 11
Pages: 7279–7290
Citations: 5
Title: Deep Echo State Network with Multiple Adaptive Reservoirs for Time Series Prediction
Authors: Wang, Z.; Yao, X.; Huang, Z.; Liu, L.
Journal: IEEE Transactions on Cognitive and Developmental Systems
Year: 2021
Volume: 13
Issue: 3
Pages: 693–704
Citations: 21
Title: A stability criterion for discrete-time fractional-order echo state network and its application
Authors: Yao, X.; Wang, Z.; Huang, Z.
Journal: Soft Computing
Year: 2021
Volume: 25
Issue: 6
Pages: 4823–4831
Research Timeline
Zhanjun Huang’s research trajectory has evolved over the years, with significant contributions made across various stages of his academic and professional journey. From his early work in communication engineering during his bachelor’s studies to his current focus on machine learning and fault diagnosis for electromechanical systems, each phase of his research timeline represents a progression towards deeper expertise and broader impact in the field of electrical engineering.
