Faculty

Name：Jing Li

Title：Lecturer

Supervisor Type: Master's Supervisor

Email：jing_li(at)tju.edu.cn

Personal Website：iamjingli.github.io

Office：Room 307, Building 8, Computer Vision Institute

Telephone：86-022-60216865

Jing Li is currently a Lecturer at School of Computer Science and Engineering, Tianjin University of Technology (TUT). He is a member of the Institute of Computer Vision led by Prof. Shengyong Chen and Prof. Jianhua Zhang. Before joining TUT in the fall of 2023, he earned the Ph.D. degree in Computer Science and Technology under the supervision of Prof. Qinghua Hu at the College of Intelligence and Computing, Tianjin University. During his Ph.D. study, he also collaborates with Prof. Liu Yang and Prof. Qilong Wang. Currently, he recruits and co-supervises one or two master students with other professors every year. Undergraduate students are also welcomed to join his research group. Please drop him an email if you’re interested in choosing him as your supervisor or working with him.

His research interests lie in the realm of machine learning and computer vision, with a distinct emphasis on developing models and algorithms tailored for real-world scenarios where the abilities to generalize and remain robust are of paramount importance. These scenarios include domain adaptation, open-set recognition, and more.

Dr. Li is currently leading 1 provincial/ministerial-level (or above) research project, undertaking 1 horizontal research project, and has been selected for 1 Key Project of the Interdisciplinary Research Support Program for Young Scholars' at TUT.

1. Pan Liu; Jing Li; Meng Zhao; Wanli Xue; Qinghua Hu; Shengyong Chen; Domain-Division based Progressive Learning for Source-Free Domain Adaptation, IEEE Transactions on Multimedia, vol. 27, pp. 7081-7092, 2025. (CAS SCI Q1 Journal, Corresponding Author)

2. Jing Li; Liu Yang; Qinghua Hu; Enhancing Multi-Source Open-Set Domain Adaptation through Nearest Neighbor Classification with Self-Supervised Vision Transformer, IEEE Transactions on Circuits and Systems for Video Technology, vol. 34, no. 4, pp. 2648-2662, 2024. (CAS SCI Q1 Journal, First Author)

3. Jing Li; Liu Yang; Qilong Wang; Qinghua Hu; WDAN: A Weighted Discriminative Adversarial Network With Dual Classifiers for Fine-Grained Open-Set Domain Adaptation, IEEE Transactions on Circuits and Systems for Video Technology, vol. 33, no. 9, pp. 5133-5147, 2023. (CAS SCI Q1 Journal, First Author)

4. Jing Li; Liu Yang; Qilong Wang; Qinghua Hu; Coarse Helps Fine: A Multi-Granularity Discriminative Adversarial Network for Fine-Grained Open-Set Domain Adaptation, IEEE International Conference on Multimedia and Expo 2023, Brisbane, Australia, July 10-14, 2023. (CCF Recommended International Conference, First Author)

5. Jing Li; Liu Yang; Qinghua Hu; Self-Supervised Vision Transformer Based Nearest Neighbor Classification for Multi-Source Open-Set Domain Adaptation, Pacific Rim International Conference on Artificial Intelligence 2022, Shanghai, China, November 10-13, 2022. (CCF Recommended International Conference, First Author)

1. The Principles of the Computer Operating System (Undergraduate, Autumn Semesters)

2. The Principles of the Compiler (Undergraduate, Spring Semesters)

1. Outstanding Graduate Student, 2017.

2. Best Presentation Award, Machine Learning Session, IEEE International Conference on Computer and Communications 2016.