Position: Distinguished Researcher
Supervisor: Doctoral students and master’s students
Office: 514, Tongxin Building, Jiading Campus
Email: wangtiange@tongji.edu.cn
Department: Maglev Transportation Engineering R&D Center
Research Directions: Image processing, high-dimensional data analytics and visualization, railway track health condition monitoring
Courses:“Intelligent Rail Transit”, “Numerical Calculation Methods”
Long-term recruitment of doctoral students, master's students and outstanding undergraduate interns, majoring in vehicle application engineering. If you are interested in the above research directions and have strong self-motivation, please contact me by email wangtiange@tongji.edu.cn.
Professional Experience
Reviewer
2023 TPC Member of IEEE Intelligent Vehicles Symposium 2023
2023-present IEEE Transactions on Intelligent Transportation Systems
2022- present Reliability Engineering & System Safety
2021- present Journal of Intelligent Manufacturing
2021- present Microprocessors and Microsystems
Educational Experience
2018.09-2022.10 PhD in Data Science, City University of Hong Kong
2014.09-2018.06 BEng in Industrial Engineering, Nanjing University
Work Experience
2023.11-present Distinguished Researcher, Institute of Rail Transit, Tongji University
2023.04-2023.07 Associate Researcher, Shenzhen Research Institute, City University of Hong Kong
2022.10-2023.03 Postdoc in Advanced Design and Systems Engineering, City University of Hong Kong
Research Project
2023.01-2025.12 Monitoring and Predictive Analysis of the External Health Condition of Railway Tracks, Shanghai Leading Talents Project
Publications
[1] T. Wang, Z. Zhang*, K. L. Tsui (2023). PFFN: Periodic Feature-Folding Deep Neural Network for Traffic Condition Forecasting. IEEE Internet of Things Journal. (JCR Q1, SCI一区top, IF 10.127)
[2] T. Wang, Z. Zhang*, K. L. Tsui (2023). CAMV: A Crash Alarm Model for Vehicles Based on Internet of Vehicles Data. IEEE Transactions on Intelligent Transportation Systems. (JCR Q1, SCI一区top, IF 7.253)
[3] T. Wang, Z. Zhang*, K. L. Tsui (2022). A Deep Generative Approach for Rail Foreign Object Detections via Semi-supervised Learning. IEEE Transactions on Industrial Informatics. (JCR Q1, SCI一区top, IF 10.215)
[4] T. Wang, Z. Zhang*, F. Yang, K. L. Tsui (2022). Automatic Rail Component Detection Based on AttnConv-Net. IEEE Sensors Journal, 3, 2379-2388. (JCR Q1, SCI二区top, IF 3.441)
[5] L. Zhuang, H. Qi, T. Wang*, Z. Zhang* (2022). A Deep Learning Powered Near Real-time Detection of Railway Track Major Components: A Two-stage Computer Vision Based Method. IEEE Internet of Things Journal. (JCR Q1, SCI一区top, IF 10.127)