Ding Li (李 丁)

Ding Li received his Ph.D. degree in Computer Science from Nanjing University in 2023. Now he serve as a lecturer in School of Computer Science, Hubei University.

Research Area: Encrypted traffic classification, Graph sketch, Deep learning

Email: liding AT hubu.edu.cn

Last update: Sep, 2026

Teaching

• Deep Learning (2026 Fall)
• Introduction to Artificial Intelligence (2026 Spring, rated excellent in teaching evaluation)
• Deep Learning (2025 Fall, rated excellent in teaching evaluation)
• Introduction to Artificial Intelligence (2025 Spring, rated excellent in teaching evaluation)
• Deep Learning (2024 Fall)
• Artificial Intelligence and Its Applications (2024 Spring, rated excellent in teaching evaluation)
• Artificial Intelligence Experiments (2024 Spring)

Research Paper

• Ding Li, Yanxing Guo, Ruyu Xie, Junya Chai, Sitong Yu, Yan Zhang, and Jun Wang. Improving Encrypted Traffic Classification with Multi-Scale Graph Sequences. In WISE'26: The 27th International Conference on Web Information Systems Engineering, Venice, Italy, November 1-5, 2026.
• Sitong Yu, Ding Li, Junya Chai, Xinyi Yu, Shiyi Li, Xiang Yin, and Yan Zhang. Enhancing Encrypted Traffic Classification with Interpretable Traffic Graph Sketches. In WISE'26: The 27th International Conference on Web Information Systems Engineering, Venice, Italy, November 1-5, 2026.
• Sitong Yu, Ding Li, Yanxing Guo, Ruyu Xie, and Yan Zhang. Encrypted Traffic Classification with Graph Sketch-Based Traffic Representation. In IJCNN'25: 2025 International Joint Conference on Neural Networks, Rome, Italy, June 30-July 5, 2025. PDF Download
• Ding Li, Wenzhong Li, Guoqiang Zhang, Yizhou Chen, Xu Zhong, Mingkai Lin, and Sanglu Lu. Dichotomy Graph Sketch: Summarizing Graph Streams with High Accuracy Based on Deep Learning. In Applied Sciences-Basel, 2023; 13(24):13306. PDF Download
• Ding Li, Wenzhong Li, Yizhou Chen, Xu Zhong, Mingkai Lin, and Sanglu Lu. Learning-based Dichotomy Graph Sketch for Summarizing Graph Streams with High Accuracy. In KSEM'23: The 16th International Conference on Knowledge Science, Engineering and Management, Guangzhou, China, August 16-18, 2023. Best Student Paper Runner Up Award. PDF Download
• Mingkai Lin, Wenzhong Li, Ding Li, Yizhou Chen, Guohao Li, Sanglu Lu. Multi-Domain Generalized Graph Meta Learning. In AAAI'23: The 37th AAAI Conference on Artificial Intelligence, Washington, USA, Feb 7-14, 2023.
• Mingkai Lin, Wenzhong Li, Ding Li, Yizhou Chen, and Sanglu Lu. Resource-Efficient Training for Large Graph Convolutional Networks with Label-Centric Cumulative Sampling. In WWW'22: The ACM Web Conference 2022, Online, April 25-29, 2022.
• Ding Li, Wenzhong Li, Yizhou Chen, Mingkai Lin, and Sanglu Lu. Learning-based Dynamic Graph Stream Sketch. In PAKDD'21: The 25th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Online, May 11-14, 2021. PDF Download
• Ding Li, Wenzhong Li, Xiaoliang Wang, Cam-Tu Nguyen, and Sanglu Lu. App Trajectory Recognition over Encrypted Internet Traffic based on Deep Neural Network. In Computer Networks, 2020; 179:107372. PDF Download
• Ding Li, Wenzhong Li, Xiaoliang Wang, Cam-Tu Nguyen, and Sanglu Lu. ActiveTracker: Uncovering the Trajectory of App Activities over Encrypted Internet Traffic Streams. In SECON'19: The 16th IEEE International Conference on Sensing, Communication, and Networking, Boston, Massachusetts, USA, June 10-13, 2019. PDF Download

Education & Work Experience

People

• Graduate students: 綦美, 肖心怡, 柴俊雅, 李诗怡, 喻新怡, 谢如玉, 郭艳星, 陆中意
• Undergraduate students: (2025级) 潘婧暄, 李元群, 宋坦育, 郑松萍, 熊威然; (2024级) 黄紫燕, 万闪闪, 程思颖, 翟雨风, 张胜彬, 余任敖; (2023级) 尹湘, 余思彤, 刘坤, 张其凌, 李新满, 刘衍崧, 熊本强
• Alumni: 杨雪 (2025 B.E., 获校级优秀毕业论文奖), 程高敏 (2025 B.E.), 舒聪聪 (2025 B.E.), 夏翔 (2025 B.E.), 徐林夕 (2025 B.E.), 陈雅宁 (2025 B.E.), 刘雨婷 (2024 B.E.), 谢振坤 (2024 B.E.), 朱靖泽 (2024 B.E.)