Welcome to College of Control Science and Engineering

Tianbao Li

Author:Publisher:李芳Update Date:2025-09-10View Times:10

»Full NameTianbao Li

»AffiliationAutomation

» Academic degreePh.D.

» TitleLecturer

» MajorInformation and Communication Engineering

» Tutor categoryNone  

»E-maillitianbao@upc.edu.cn

» Tel+86-17864237882

Research Areas

My research focuses on machine learning theories such as physics-informed deep learning, spatiotemporal sequence forecasting, and transfer learning, with applications in intelligent marine meteorological prediction, 3D object recognition, and AI4Science-related fields.

(1) Self-motivated graduate students interested in artificial intelligence research are welcome to join our team!

Group Homepage: https://www.scholat.com/team/weifengliugroup

(2) Undergraduate students from all backgrounds are encouraged to intern, collaborate, or exchange ideas in our lab!

If you are passionate about using AI to solve scientific problems, feel free to contact me!


Education

2019.09–2025.06: Ph.D. in Information and Communication Engineering (Direct Ph.D. track), Tianjin University

2015.09–2019.06: B.E. in Electronic and Information Engineering (Experimental Class), China University of Petroleum (East China)


Employment

2025.09-present: Lecturer, College of Control Science and Engineering, China University of Petroleum (East China)


Courses Offered

None


Guiding graduate students

None


Funding and Projects

Participated in:

[1] NSFC Joint Key Program: “Knowledge Evolution Representation and Collaborative Reasoning for Marine Big Data” (No. U23A20320), 2024.01-2027.12.

[2] NSFC Joint Key Program: “Intelligent Supercomputing Models and Algorithms for Cross-Modal Marine Big Data Applications” (No. U22A2068), 2023.01-2026.12.

[3] National Key R&D Program of China: “Scenario-Driven Key Technologies and Applications for Marine Science Big Data Mining and Analysis” (No. 2021YFF0704000), 2022.01-2024.12.


Awards & Honors

None


Representative Publications

[1] Tianbao Li, Yuting Su, Dan Song*, et al. Multi-Scale Spatial-Temporal Transformer for Meteorological Variable Forecasting. IEEE TCSVT, 2025, 35(3): 2474–2486.

[2] Tianbao Li, An-an Liu, Dan Song, et al. Multi-Task Spatial-Temporal Transformer for Multi-Variable Meteorological Forecasting. IEEE TKDE, 2024, 36(12): 8876–8888.

[3] Tianbao Li, Yuting Su, Dan Song*, et al. Progressive Fourier Adversarial Domain Adaptation for Object Classification and Retrieval. IEEE TMM, 2024, 26: 4540–4553.

[4] An-an Liu, Haochun Lu, Heyu Zhou, Tianbao Li, Mohan Kankanhalli. Balanced Class-Incremental 3D Object Classification and Retrieval. IEEE TKDE, 2024, 36(1): 35–48.

[5] Tianbao Li, An-an Liu, Dan Song, et al. Focus on Hard Samples: Hierarchical Unbiased Constraints for Cross-Domain 3D Model Retrieval. IEEE TCSVT, 2023, 33(11): 7036–7049.

[6] Jie Nie, Ting Zhang, Tianbao Li, et al. Image-based 3D model retrieval via disentangled feature learning and enhanced semantic alignment. Information Processing & Management, 2023, 60(2): 103159.

[7] Dan Song, Yuting Ling, Tianbao Li*, et al. Gradual adaption with memory mechanism for image-based 3D model retrieval. Image and Vision Computing, 123: 104482.

[8] Dan Song, Tianbao Li, Wenhui Li, et al. Universal Cross-Domain 3D Model Retrieval. IEEE TMM, 2021, 23: 2721–2731.

[9] Dan Song, Tianbao Li, Zhendong Mao, et al. SP-VITON: shape-preserving image-based virtual try-on network. Multimedia Tools and Applications, 2020, 79(45): 33757–33769.

[10] An-an Liu, Tianbao Li, Dan Song, et al. Research Progress on Prediction Methods of Marine Extreme Weather Phenomena. Journal of Data Acquisition and Processing, 2023, 38(2): 231–244. (in Chinese)


Patent

[1] An-an Liu, Tianbao Li, Dan Song, et al. Cross-domain object recognition method based on intermediate domain guidance and metric learning constraints. Granted, ZL202311757258.1.

[2] An-an Liu, Tianbao Li, Dan Song, et al. Meta-learning-based method and device for El Niño extreme weather warning. Granted, ZL202210703932.7.

[3] An-an Liu, Tianbao Li, Dan Song, et al. Multimodal graph convolutional network-based method for social network event detection. Granted, ZL202110265390.5.