👋 About Me
I am a Ph.D. student in the Department of Mechanical Engineering at Tsinghua University, supervised by Prof. Zhaoye Qin. My previous experiences include:
- Apr 2025 - Sep 2025, Visiting scholar at Yale University，collaborating with Lu Lu.
- Apr 2022 - Sep 2022, Research intern at AIR, Tsinghua University, supervised by Yuanchun Li.
- Sep 2019 - Jun 2022, M.Eng. in Control Theory and Control Engineering at Soochow University (SUDA), supervised by Prof. Liang Chen and Prof. Changqing Shen.
- Sep 2015 - Jun 2019, B.Eng. in Electrical Engineering at SUDA.
My research interests including trustworthy AI, foundation model and reliable prognostic and health management (PHM). I have published numerous papers in top-tier international journals with total google scholar citations 500+. Feel free to reach out for collaboration opportunities!
🔥 News
- 2025.01: A paper accepted by ADVEI
- 2025.01: The 2024 CAST Youth Talent Support Program - PhD Special Plan - CCF
- 2024.12: Science and Technology Award of Chinese Society of Vibration Engineering.
- 2024.11: A paper accepted by JMS.
- 2024.02: A paper accepted by IEEE TII.
- 2022.05: Received the Future Scholars Scholarship from THU.
📝 Publications
🔖Neural-symbolic Diagnosis
Deep Expert Network: A Unified Method toward Knowledge-Informed Fault Diagnosis via Fully Interpretable Neuro-Symbolic AI
Qi Li, Yuekai Liu, Shilin Sun, Zhaoye Qin, Fulei Chu
- Proposes a neuro-symbolic AI approach to fault diagnosis incorporating interpretable expert knowledge using a Deep Expert Network. (JCR Q1, Impact Factor: 12.2)
Transparent Operator Network: A Fully Interpretable Network Incorporating Learnable Wavelet Operator for Intelligent Fault Diagnosis
Qi Li, Hua Li, Wenyang Hu, Shilin Sun, Zhaoye Qin, Fulei Chu
- This work introduces an interpretable method for industrial time series classification by integrating learnable wavelet operators. (JCR Q1, Impact Factor: 12.3)
🔖 Cross-domain Diagnosis
Cross-Domain Augmentation Diagnosis: An Adversarial Domain-Augmented Generalization Method for Fault Diagnosis under Unseen Working Conditions
Qi Li, Liang Chen, Lin Kong, Dong Wang, Min Xia, Changqing Shen
- This paper presents a domain generalization approach employing adversarial learning and data augmentation for robust industrial time series classification. (JCR Q1, Impact Factor: 9.4)
Adversarial Domain-Invariant Generalization: A Generic Domain-Regressive Framework for Bearing Fault Diagnosis under Unseen Conditions
Chen Liang, Qi Li, Changqing Shen, Jun Zhu, Dong Wang, Min Xia
- A generic domain-regressive framework for fault diagnosis using adversarial learning between feature extractors and domain classifiers, achieving robust diagnosis performance. (JCR Q1, Impact Factor: 11.7, highly cited🌟)
Knowledge Mapping-Based Adversarial Domain Adaptation: A Novel Fault Diagnosis Method with High Generalizability under Variable Working Conditions
Qi Li, Changqing Shen, Liang Chen, Zhongkui Zhu
- Introduces a domain adaptation strategy using adversarial learning for improved generalizability in fault diagnosis across variable conditions. (JCR Q1, Impact Factor: 7.9, highly cited🌟)
- Enhanced Generative Adversarial Networks for Fault Diagnosis of Rotating Machinery with Imbalanced Data, Measurement Science and Technology, 2019
Qi Li, Liang Chen, Changqing Shen et al.
🔖PHM foundation model
- TODO
🎖 Honors and Awards
- 2023: Social Practice Scholarship of Tsinghua University
- 2022: Future Scholars Scholarship of Tsinghua University
- 2021: National Scholarship by Ministry of Education of China
- 2021: Outstanding Student Cadre of Jiangsu Province
- 2021: Outstanding postgraduate cadre of Soochow University
- 2020: National Scholarship by Ministry of Education of China
- 2020: Outstanding postgraduate of Soochow University
- 2019: Special Award of Graduate Academic Scholarship
- 2019: Delivered a speech at the opening ceremony of SUDA as a graduate student representative
- 2019: Outstanding graduate of Soochow University
📖 Educations
- 2025.04 - 2025.09, Visiting scholar in Statistics and Data Science, Yale University, advisor: Lu Lu.
- 2022.09 - Present, Ph.D. in Mechanical Engineering, Tsinghua University (THU), Supervisor: Prof. Zhaoye Qin
- 2019.09 - 2022.06, M.E. in Control Theory and Control Engineering, Soochow University (SUDA), Supervisors: Prof. Liang Chen, Prof. Changqing Shen
- 2015.09 - 2019.06, B.E. in Electrical Engineering, Soochow University (SUDA)
💬 Invited Talks
- 2024.04, Beijing AI PhD Student Forum, Beijing, China (2w viewers)
- 2023.11, PHM Conference, Hangzhou, Hangzhou, China
- 2023.04, Tsinghua University Department of Mechanical Engineering PhD Student Forum
- 2020.07, IEEE INDIN 2020, Warwick, UK
- 2018.07, SDPC 2018, Xi’an, China
💻 Internships
- Mar 2022 - Aug 2022, Research Intern at Institute for AI Industry Research, Tsinghua University
- Conducted a research project focused on AI-enabled time series analysis for battery monitoring.
🔧 Skills
- Language: CSC English test (104/130)
- Programming: Python, MATLAB, PyTorch, TensorFlow
- Hobby: Marathon, Positive Psychology, Workout
🖥 Journal Reviews
- Mechanical Systems and Signal Processing (MSSP)
- IEEE Transactions on Industrial Electronics (TIE)
- IEEE Transactions on Instrumentation and Measurement (TIM)
- IEEE Transactions on Industrial Informatics (TII)
- Measurement
- Measurement Science and Technology (MST)
💴 Horizontal project
- TODO after graduation.
🎙 Social Activities
- 2023：Volunteer at the IFToMM International Conference on Rotordynamics
- 2019 - 2022: Graduate monitor of the University of Mechanical and Electric Engineering, SUDA
- 2021: Interview by Student Union of Soochow University Link
- 2019: Delivered a speech at the opening ceremony of SUDA as a graduate student representative Link
📫 Contact
🎈 Myself
- Email: liq22@mails.tsinghua.edu.cn
- ORCID: https://orcid.org/0000-0001-7105-2818
- wechat: 17777777
- [Curriculum Vitae]