Dr. Thierry Boileau | System Surveillance Awards | Best Scholar Award

Dr. Thierry Boileau | System Surveillance Awards | Best Scholar Award

Dr. Thierry Boileau, University of Lorraine, France

Thierry Boileau is an Assistant Professor at the University of Lorraine in France, specifically within the École Nationale Supérieure d’Électricité et de Mécanique (ENSEM) and the Laboratoire d’Énergétique et de Mécanique Théorique et Appliquée (LEMTA). He earned his Ph.D. in Electrical Engineering from INPL Nancy in 2010, with a dissertation focused on the continuity of service for synchronous actuators with permanent magnets, addressing mechanical sensor faults and electrical defect detection. He also holds a Master’s degree in Electrical Engineering from Nancy University and a prestigious French teaching degree, Agrégation de Sciences Physiques.

Professional Profile:

ORCID

Summary of Suitability for Best Scholar Award: Thierry Boileau

Thierry Boileau demonstrates outstanding qualifications for the Best Scholar Award based on his exceptional academic and research achievements in electrical engineering. Below is a detailed evaluation of his suitability

🎓 Academic Education:

  • Ph.D. in Electrical Engineering (2010, INPL Nancy, France)
    • Thesis Title: “Contribution to the Service Continuity of Synchronous Actuators with Permanent Magnets: Tolerance to Mechanical Sensor Failure and Electrical Fault Detection”
  • Master’s Degree in Electrical Engineering (2004, Nancy University, France)
  • French Teaching Degree (Agrégation de Sciences Physiques, 1999)

📚 Background and Achievements:

  • Publications:
    • 19 journal papers (mainly in IEEE Transactions)
    • 20 international conference papers
  • Research Impact:
    • H-index: 15 (as of November 2023, source: Scopus)
    • Citations: 1,337 (as of November 2024, source: Google Scholar)

👨‍🎓 Research Supervision:

  • Master’s Degree Students: 2
  • Ph.D. Students: 7 (3 defended theses and 4 ongoing)

🤝 Industrial Partnerships:

  • Collaborations with 5 industrial partners (including SAFRAN, EADS, SEW, CNC-SNR, etc.)
  • 4 industrial contract reports

🔬 Research Activities:

Thierry’s primary research interests include:

  • Diagnostics and Control of Electrical Machines supplied by static converters.
  • Energy Carrier Management and microgrid technologies.

Publication Top Notes:

Online High Frequency Impedance Identification Method of Inverter-Fed Electrical Machines for Stator Health Monitoring

Comparison of high frequency winding modeling for stator health monitoring

Optimal performance identification of a combined free piston Stirling engine with a permanent magnet linear synchronous machine using dedicated controls

PMASynRM Local Demagnetization Fault Behavior Study Under Targeted Harmonic Excitation

A New Coupled Approach for Enthalpy Pumping Consideration in a Free Piston Stirling Engine (FPSE)

Introducing a New System for Energy Recovery of High and Mid-Temperature Renewable Energy Sources: Free Piston Stirling Engine Combined with a Permanent Magnet Linear Synchronous Machine

 

 

 

 

Mr. Zhongzhi Li | Fault Detection Awards | Best Researcher Award

Mr. Zhongzhi Li | Fault Detection Awards | Best Researcher Award

Mr. Zhongzhi Li, Fudan University, China

Zhongzhi Li, is a male graduate student specializing in Aeronautics and Astronautics at Fudan University, where he maintains a GPA of 3.41/4.0, ranking 1st among 45 students. His academic journey began at Shenyang Aerospace University, where he earned a Bachelor’s degree in Computer Science and Technology, achieving an impressive GPA of 93/100 and ranking 1st out of 155. Zhongzhi has published three first-author papers in SCI-indexed journals and has applied for a patent, reflecting his research focus on time series analysis. He has received several scholarships, including the National Scholarship and the Zhang Mingwei Inspirational Scholarship. His practical experience includes internships as an AI Engineer Intern at Huawei Technologies, where he developed predictive models for cloud services, and as an Algorithm Intern at Gotion High-tech, where he created algorithms for battery fault prediction with high accuracy. Zhongzhi also served as a student assistant at Fudan University’s Party Building Service Center and currently leads the Graduate Student Union’s Practice Department. In addition to his academic pursuits, he is an avid sports enthusiast, enjoying basketball, volleyball, and running, and has participated in several marathons, including the 2022 Shanghai Half Marathon.

Professional Profile:

GOOGLE SCHOLAR

Summary of Suitability for the Best Researcher Award: Zhongzhi Li

Academic Excellence and Research Experience: Zhongzhi Li demonstrates a strong academic foundation and expertise in both time series analysis and fault detection in various engineering applications. His achievements at Fudan University, where he ranks 1st out of 45 peers with a GPA of 3.41/4.0, along with his numerous scholarships (National Scholarship, Zhang Mingwei Inspirational Scholarship, etc.), reflect his academic dedication and capabilities. His undergraduate performance was equally impressive, ranking 1st out of 155 students at Shenyang Aerospace University.

Education

Fudan University
Master of Science in Aeronautics and Astronautics
Duration: September 2022 – June 2025

  • GPA: 3.41/4.0
  • Rank: 1/45
  • Scholarships: National Scholarship, Freshman Scholarship, Zhang Mingwei Inspirational Scholarship, Zhang Yongming Scholarship

Shenyang Aerospace University
Bachelor of Science in Computer Science and Technology
Duration: September 2018 – June 2022

  • GPA: 93/100
  • Rank: 1/155
  • Scholarships: National Scholarship, “Top Ten Figures of the Year” at SAU, Six Academic Excellence Scholarships, Enterprise Scholarships

Work Experience

Huawei Technologies Co., Ltd.
AI Engineer Intern, Huawei Cloud Algorithm Innovation Lab
Duration: July 2023 – August 2023

  • Analyzed current usage data on Huawei Cloud, visualizing trends in VM core counts and types using stacked area charts.
  • Developed a multimodal XAI predictive model for VM request sequence forecasting, integrating large-scale semantic information. Utilized an improved Transformer-based algorithm, achieving less than 10% prediction error on monthly and yearly scales.

Gotion High-tech Co., Ltd.
Algorithm Intern, Big Data Engineering Department
Duration: September 2022 – March 2023

  • Developed supervised and unsupervised algorithms for predicting thermal runaway faults in lithium and ternary lithium batteries, achieving detection accuracy above 95%.
  • Proposed an improved thermal runaway detection algorithm using Stacking, achieving nearly 100% accuracy, which was successfully deployed on Alibaba Cloud PAI.

Dongguan Securities Co., Ltd.
Research Intern, Quantitative Investment Department
Duration: May 2022 – August 2022

  • Managed FTP data downloads (30GB) using verification scripts to tackle large data volume and speed limits.
  • Conducted stock data preprocessing and historical data analysis with Python and C++. Practiced basic quantitative investment strategies, including dual moving average, multi-factor stock selection, Bollinger Bands, and PEG strategies.

Fudan University Party Building Service Center
Student Assistant
Duration: September 2022 – July 2023

Fudan University Department of Aeronautics and Astronautics
Head of Graduate Student Union Practice Department / Office Assistant
Duration: September 2023 – September 2024

Publication top Notes:

CITED:83
CITED:57
CITED:56
CITED:30
CITED:21
CITED:21

 

Prof. Tonghai Wu | Lubrication Monitoring Award | Best Researcher Award

Prof. Tonghai Wu | Lubrication Monitoring Award | Best Researcher Award

Prof. Tonghai Wu, Xi’an Jiaotong University, China

Prof. Tonghai Wu has been a distinguished member of Xi’an Jiaotong University (XJTU) since 2006. He completed his postdoctoral research at the Materials Science and Engineering Postdoctoral Station (XJTU) from 2008 to 2010. During 2013-2014, he was a visiting scholar at UNSW, where he collaborated with Prof. Peng on condition monitoring and built partnerships with Doc. Ngai Ming Kwok and Prof. Weihua Li on image processing and wear particle sensor technology. In January 2017, he was appointed professor at the School of Mechanical Engineering at XJTU and became the Dean in 2024. He currently leads the Machine Condition Monitoring research group at XJTU, guided by Prof. Yaguo Lei.

Professional Profile:

Summary of Suitability for the Best Researcher Award:

  • Professor Wu’s research expertise includes wear analysis, condition monitoring of mechanical systems, online monitoring technologies, and the development and application of artificial intelligence techniques for predicting performance and remaining useful life of mechanical systems. His research also integrates multiple techniques such as wear analysis, vibration, and oil monitoring for machine health monitoring.

Research Interests:

🔬 Prof. Wu specializes in wear analysis and condition monitoring of mechanical systems. His work focuses on:

  • On-line monitoring technologies for lubrication films and wear debris
  • In-situ inspection technologies using 3D image acquisition
  • Development and application of AI techniques for performance prediction and lifespan assessment
  • Integration of wear analysis, vibration, and oil monitoring for machine health

Field of Research (FoR):

  • Tribology
  • Dynamics, Vibration, and Vibration Control
  • Artificial Intelligence and Image Processing

Research Collaboration:

Prof. Wu collaborates extensively with researchers globally, including in the United States, Austria, and Britain, on fundamental and applied tribology and machine condition monitoring projects.

Awards and Service to the Profession:

🏆 Competitive Grants: Secured nearly 20 million RMB in funding for research on wear debris and condition monitoring.
🔧 Consultancy: Developed integrated on-line monitoring systems for wind turbines and ocean dredger ships. Consulted for major companies in wind power, oil refining, mining, and civil engineering.
🔬 Professional Activities: Reviewed manuscripts for top journals and served as a peer reviewer for NSFC. Member of the Society of Tribologists and Lubrication Engineers and China Mechanical Engineering Society. Guest Editor for the International Journal of Rotating Machinery.

Research Impact:

📚 Prof. Wu has published over 90 high-quality papers, with over 50% in top journals, and garnered more than 2,000 citations over the past decade.

Publication top Notes:

An integrated knowledge and data model for adaptive diagnosis of lubricant conditions

Ultrasonic reflection measured oil film thickness in the slipper bearings of an aviation fuel piston pump

Spatial-temporal modeling of oil condition monitoring: A review

Fully unsupervised wear anomaly assessment of aero-bearings enhanced by multi-representation learning of deep features

Optimized Mask-RCNN model for particle chain segmentation based on improved online ferrograph sensor

Comparison-embedded evidence-CNN model for fuzzy assessment of wear severity using multi-dimensional surface images

 

Mr. Yongchao Hui | System diagnostics Award | Best Researcher Award

Mr. Yongchao Hui | System diagnostics Award | Best Researcher Award

Mr. Yongchao Hui, Nanjing University of Aeronautics and Astronautics, China

Yongchao Hui is a Ph.D. candidate in Control Science and Engineering at Nanjing University of Aeronautics and Astronautics, specializing in the advanced health assessment, lifespan prediction, and fault diagnosis of aerospace components. His research contributions, highlighted by numerous publications in high-impact SCI journals like Aerospace and Applied Sciences-Basel, have introduced groundbreaking methodologies, including the use of multiparametric data distribution characteristics and the Wasserstein Distance for satellite component health assessments. These innovations have significantly advanced the field of aerospace engineering.

Professional Profile:

Summary of Suitability for Best Researcher Award:

Yongchao Hui is a distinguished Ph.D. candidate in Control Science and Engineering at Nanjing University of Aeronautics and Astronautics, with a research focus on the advanced health assessment, lifespan prediction, and fault diagnosis of aerospace components. His work has led to significant innovations in the field, particularly through his development of methodologies that utilize multiparametric data distribution characteristics and the Wasserstein Distance for satellite component health assessments. These contributions have not only advanced the state of aerospace engineering but have also been recognized through publications in high-impact SCI journals such as Aerospace and Applied Sciences-Basel.

Education:

  1. Ph.D. in Control Science and Engineering (In Progress)
    • Institution: Nanjing University of Aeronautics and Astronautics
    • Focus: Advanced health assessment, lifespan prediction, and fault diagnosis of aerospace components.
    • Notable Achievements:
      • Published several papers in high-impact SCI journals, including Aerospace and Applied Sciences-Basel.
      • Developed innovative methodologies using multiparametric data distribution characteristics and the Wasserstein Distance for satellite component health assessments.
  2. Bachelor’s Degree in [Field]
    • Institution: [Name of University]
    • Notable Achievements:
      • Awarded the Shanghai Municipal Scholarship.
      • Lead role in the SEMG-based Lower Limb Rehabilitation Robot project, earning the “Internet+” Bronze Award.

Work Experience:

  1. Ph.D. Candidate and Researcher (Present)
    • Institution: Nanjing University of Aeronautics and Astronautics
    • Responsibilities:
      • Designing and validating component-system-level health assessment algorithms.
      • Conducting research on consistency theory, swarm intelligence algorithms, and machine learning techniques for aerospace applications.
      • Developed real-time health assessment algorithms for critical satellite components.
    • Notable Contributions:
      • Significant improvements in reliability and accuracy of health assessment algorithms.
      • Key contributor to major research projects, including those at the China Academy of Space Technology.
  2. Research Contributor (During Ph.D. Program)
    • Institution: China Academy of Space Technology
    • Responsibilities:
      • Developed real-time health assessment algorithms for satellite components.
      • Worked on projects directly impacting mission success in aerospace engineering.

Additional Technical Skills:

  • Proficient in microcontroller development, motor speed control, and various programming languages.
  • Experience in developing sophisticated data analysis software for fault diagnosis and lifespan prediction models.

Awards and Recognition:

  • National Scholarship for Graduate Students.
  • “Outstanding Graduate of Nanjing University of Aeronautics and Astronautics.”
  • Graduate Student Mathematics Modeling Competition award at Nanjing University of Aeronautics and Astronautics.

Publication top Notes:

A Novel Approach to Satellite Component Health Assessment Based on the Wasserstein Distance and Spectral Clustering

A Method for Satellite Component Health Assessment Based on Multiparametric Data Distribution Characteristics