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:

Series arc fault detection of indoor power distribution system based on LVQ-NN and PSO-SVM

CITED:83

Wasserstein Generative Adversarial Network and Convolutional Neural Network (WG‐CNN) for Bearing Fault Diagnosis

CITED:57

Fault detection on insulated overhead conductors based on DWT-LSTM and partial discharge

CITED:56

Wildland fire burned areas prediction using long short-term memory neural network with attention mechanism

CITED:30

Multi-parameter fire detection method based on feature depth extraction and stacking ensemble learning model

CITED:21

Partial discharge detection of insulated conductors based on CNN-LSTM of attention mechanisms

CITED:21

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.

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:

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.

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:

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.

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.