Professor at Fudan University, China
Prof. Dr. Cheng-Wei Fei is a distinguished academic and researcher specializing in aerospace engineering, particularly in aeroengine structural strength and reliability. He is currently a Professor at Fudan University, with prior experience as a Research Fellow at Hong Kong University of Science and Technology and as a Postdoctoral Fellow at Hong Kong Polytechnic University. With a Ph.D. in Aerospace Propulsion Theory and Engineering from Beihang University, Prof. Fei has published over 130 SCI-indexed papers and authored six books. His research contributions, including 15 patents, focus on AI-driven advancements in aircraft health management and reliability, directly supporting key national projects like the C919 and CJ-1000 aircraft. He is an active leader in the academic community, serving as an editor for several prominent journals and holding multiple leadership roles in aerospace societies. Prof. Fei’s work bridges fundamental science and practical applications, positioning him as a key figure in aerospace research and development.
Professional Profile
Education
Prof. Dr. Cheng-Wei Fei has a strong academic foundation in aerospace engineering. He earned his Ph.D. in Aerospace Propulsion Theory and Engineering from Beihang University in 2014, following a Master’s degree in the same field from Shenyang Aerospace University in 2010. His undergraduate studies were in Electrical Engineering and Automation, which he completed at Fujian University of Technology in 2007. Throughout his academic journey, Prof. Fei has continually sought to advance his knowledge, first as a student and later as a researcher and educator. His rigorous education laid the groundwork for his future contributions to aerospace science, particularly in the areas of aeroengine reliability, AI applications in aerospace, and advanced propulsion technologies. Prof. Fei’s ongoing commitment to academic excellence is reflected in his long-standing position as a Professor at Fudan University, where he continues to push the boundaries of aerospace research.
Professional Experience
Prof. Dr. Cheng-Wei Fei has extensive professional experience in both academic and research settings. He currently serves as a professor in the Department of Mechanical Engineering, specializing in the design and analysis of materials and components. Throughout his career, Dr. Fei has been involved in numerous high-impact research projects related to structural reliability, materials behavior, and dynamic system modeling. His expertise spans computational mechanics, dynamic modeling of structures, and advanced materials design, with a focus on integrating multi-physics approaches for solving real-world engineering problems. Dr. Fei has also contributed significantly to the advancement of reliability-based design optimization and surrogate modeling strategies. He has collaborated with industry partners and government organizations, applying his research to practical challenges in the aerospace, automotive, and energy sectors. With over 100 peer-reviewed publications, Dr. Fei is a leading figure in his field, recognized for his contributions to engineering design and innovation.
Research Interest
Prof. Dr. Cheng-Wei Fei’s research interests are centered around aerospace propulsion, structural strength, and reliability, with a particular focus on integrating artificial intelligence (AI) into aerospace systems. He has made significant contributions to the development of new theories and methodologies, such as information fusion fault diagnosis, dynamic assembly reliability design, and intelligent reliability design for aeroengines and aircraft. His research aims to address critical challenges in aircraft health management, intelligent operation and maintenance, and the overall reliability of aerospace technologies. Prof. Fei’s work supports the development of key national aerospace projects, including China’s C919 and CJ-1000 aircraft, as well as advanced aeroengines. He is deeply involved in applying AI and advanced engineering models to improve the performance and safety of aerospace systems, with his research outcomes directly influencing the design and operational efficiency of modern aircraft and engines. His interdisciplinary approach blends aerospace engineering with cutting-edge AI techniques, pushing the boundaries of innovation in the field.
Award and Honor
Prof. Dr. Cheng-Wei Fei has received numerous accolades for his exceptional contributions to aerospace engineering and research. He has been recognized for his groundbreaking work in aeroengine reliability, AI integration, and aerospace health management, which has significantly impacted national aerospace projects like the C919 and CJ-1000 aircraft. As an academic leader, Prof. Fei holds prestigious editorial positions in renowned journals, including Shock and Vibration, Aerospace, and Mechanical Design. He has also been invited as a session chair at major international conferences, such as AAME 2024 and ISAES 2024, further underscoring his global reputation. In addition to his academic achievements, Prof. Fei is actively involved in professional societies, holding leadership roles such as Vice Chairman of the National Committee of Experts on Aerospace Materials and Deputy Director of the Aeronautical Power Professional Committee of Shanghai Aeronautical Society. These honors reflect his significant influence and leadership in the aerospace research community.
Conclusion
Prof. Dr. Cheng-Wei Fei is highly suitable for the Best Researcher Award. His extensive research output, leadership roles, significant contributions to national aerospace projects, and strong academic background make him an outstanding candidate. Addressing the noted areas for improvement, particularly by broadening his research scope and emphasizing global impact, could further enhance his qualifications for international recognition.
Publications Top Noted
- Title: Improved Kriging with extremum response surface method for structural dynamic reliability and sensitivity analyses
Authors: C Lu, YW Feng, RP Liem, CW Fei
Year: 2018
Citations: 108
- Title: Fusion information entropy method of rolling bearing fault diagnosis based on n-dimensional characteristic parameter distance
Authors: YT Ai, JY Guan, CW Fei, J Tian, FL Zhang
Year: 2017
Citations: 102
- Title: LSTM-based multi-layer self-attention method for remaining useful life estimation of mechanical systems
Authors: J Xia, Y Feng, C Lu, C Fei, X Xue
Year: 2021
Citations: 100
- Title: Moving extremum surrogate modeling strategy for dynamic reliability estimation of turbine blisk with multi-physics fields
Authors: C Lu, CW Fei, HT Liu, H Li, LQ An
Year: 2020
Citations: 98
- Title: Probabilistic LCF life assessment for turbine discs with DC strategy-based wavelet neural network regression
Authors: LK Song, GC Bai, CW Fei
Year: 2019
Citations: 84
- Title: Multi-objective reliability-based design optimization approach of complex structure with multi-failure modes
Authors: LK Song, CW Fei, J Wen, GC Bai
Year: 2017
Citations: 81
- Title: Improved decomposed-coordinated kriging modeling strategy for dynamic probabilistic analysis of multicomponent structures
Authors: C Lu, YW Feng, CW Fei, SQ Bu
Year: 2019
Citations: 80
- Title: Multi-extremum-modified response basis model for nonlinear response prediction of dynamic turbine blisk
Authors: B Keshtegar, M Bagheri, CW Fei, C Lu, O Taylan, DK Thai
Year: 2021
Citations: 78
- Title: Reliability-based low-cycle fatigue damage analysis for turbine blade with thermo-structural interaction
Authors: H Gao, C Fei, G Bai, L Ding
Year: 2016
Citations: 77
- Title: Probabilistic analyses of structural dynamic response with modified Kriging-based moving extremum framework
Authors: C Lu, CW Fei, YW Feng, YJ Zhao, XW Dong, YS Choy
Year: 2021
Citations: 76
- Title: Enhanced network learning model with intelligent operator for the motion reliability evaluation of flexible mechanism
Authors: CW Fei, H Li, HT Liu, C Lu, LQ An, L Han, YJ Zhao
Year: 2020
Citations: 73
- Title: Multilevel nested reliability-based design optimization with hybrid intelligent regression for operating assembly relationship
Authors: CW Fei, H Li, HT Liu, C Lu, B Keshtegar, LQ An
Year: 2020
Citations: 73