Cheng-Wei Fei | Design of Materials and Components | Best Researcher Award

Prof. Dr. Cheng-Wei Fei | Design of Materials and Components | Best Researcher Award

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 ProfileΒ 

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

 

Jiyoung Kim | Material Science | Best Researcher Award

Jiyoung Kim | Material Science | Best Researcher Award

Ms. Jiyoung Kim , Seoul National University, South Korea

Publication profile

Scopus

Googlescholar

Education

  • PhD in Material Science Engineering
    Seoul National University, Korea – In progre
  • ss (2019-present)Β πŸŽ“
  • M.S. in Material Science Engineering
    Hanyang University, Korea – 2008Β πŸ“–
  • B.S. in Material Science Engineering
    Hanyang University, Korea – 2006Β πŸŽ“

Experience

  • Senior Research Engineer
    Hyundai Steel Company, Korea β€” 2019–present 🏭
  • Research Engineer
    Hyundai Steel Company, Korea β€” 2014–2018Β πŸ”
    Hyundai HYSCO, Korea β€” 2008–2013Β πŸ—οΈ

Suitability for The Award

Ji-Young Kim is a highly qualified candidate for the Best Researcher Award due to her significant contributions to material science and engineering, particularly in the field of metallic and inorganic coatings. Her extensive academic background, hands-on industry experience, and involvement in technical committees underscore her commitment to advancing research in her field.

Professional Development (πŸ’ΌπŸ”¬)

Research Focus 🧫🧬

Awards and Honors (πŸ†πŸŽ–οΈ)

  • Best Paper AwardΒ – International Conference on Coatings Technology (2021)Β πŸ…
  • Excellence in Research AwardΒ – Hyundai Steel Company (2020) 🌟
  • Outstanding Graduate Student AwardΒ – Hanyang University (2008)Β πŸŽ–οΈ
  • ISO Recognition CertificateΒ – Contribution to Technical Committee 107 (2022)Β πŸ“œ

PublicationΒ 

  • Naturally occurring phytochemicals for the prevention of Alzheimer’s diseaseΒ – J Kim, HJ Lee, KW Lee, Journal of Neurochemistry, 112 (6), 1415-1430 (2010) 🌱🧠
  • Inhibition of p38 and ERK MAP kinases blocks endotoxin-induced nitric oxide production and differentially modulates cytokine expressionΒ – SH Kim, J Kim, RP Sharma, Pharmacological Research, 49 (5), 433-439 (2004)Β πŸš«πŸ’Š
  • Caffeinated coffee, decaffeinated coffee, and the phenolic phytochemical chlorogenic acid up-regulate NQO1 expression and prevent H2O2-induced apoptosis in primary cortical neuronsΒ – J Kim, S Lee, J Shim, HW Kim, J Kim, YJ Jang, H Yang, J Park, SH Choi, Neurochemistry International, 60 (5), 466-474 (2012)Β β˜•πŸ§¬
  • Cocoa phytochemicals: recent advances in molecular mechanisms on healthΒ – J Kim, J Kim, J Shim, CY Lee, KW Lee, HJ Lee, Critical Reviews in Food Science and Nutrition, 54 (11), 1458-1472 (2014) 🍫πŸ’ͺ
  • Cocoa polyphenols suppress adipogenesis in vitro and obesity in vivo by targeting insulin receptorΒ – SY Min, H Yang, SG Seo, SH Shin, MY Chung, J Kim, SJ Lee, HJ Lee, International Journal of Obesity, 37 (4), 584-592 (2013)Β πŸ“‰πŸ©
  • Increased expression of the receptor for advanced glycation end products in neurons and astrocytes in a triple transgenic mouse model of Alzheimer’s diseaseΒ – BR Choi, WH Cho, J Kim, HJ Lee, CH Chung, WK Jeon, JS Han, Experimental & Molecular Medicine, 46 (2), e75-e75 (2014) 🧬🐭
  • Calcium-Mediated Activation of c-Jun NH2-Terminal Kinase (JNK) and Apoptosis in Response to Cadmium in Murine MacrophagesΒ – J Kim, RP Sharma, Toxicological Sciences, 81 (2), 518-527 (2004)Β βš οΈβš—οΈ
  • Silymarin Protects Against Liver Damage in BALB/c Mice Exposed to Fumonisin B1 Despite Increasing Accumulation of Free Sphingoid BasesΒ – Q He, J Kim, RP Sharma, Toxicological Sciences, 80 (2), 335-342 (2004)Β πŸ­πŸƒ