Zhenglong Ding is an Associate Professor and Master’s Supervisor at the School of Artificial Intelligence, Nanjing University of Information Science and Technology. His teaching and research focus on intelligent information processing, image processing, deep learning, pattern recognition, and the applications of related technologies.

He has led five vertical research projects, including a project funded by the National Natural Science Foundation of China, an Academic Support Program for Top-Notch Talents in University Disciplines (Majors) of the Anhui Provincial Department of Education, and a Key Natural Science Research Project of the Anhui Provincial Department of Education. He has also undertaken five horizontal research projects commissioned by enterprises and public institutions. To date, he has published more than ten academic papers as the first or corresponding author in high-impact international journals such as IEEE/ASME Transactions on Mechatronics and IEEE Transactions on Instrumentation and Measurement. He holds 14 granted national invention patents.

In terms of teaching achievements, he has received a Second Prize and a Third Prize of the Provincial Teaching Achievement Awards (both ranked first). He has supervised students participating in discipline competitions, earning six national-level awards and more than ten provincial-level awards. He has also supervised five projects under the National Undergraduate Innovation and Entrepreneurship Training Program.

He is qualified to supervise both academic and professional master’s students and welcomes motivated undergraduates with research interests in automated inspection and artificial intelligence to join his research group.

We welcome highly motivated undergraduate students who are passionate about machine vision and artificial intelligence for inspection applications. If you wish to join our research team, please feel free to reach out with your CV.

Partial List of Published Papers

[1] W. Xu, Z. Ding*, Z. Wang, et al., “Think Locally and Act Globally: A Frequency–Spatial Fusion Network for Infrared Small Target Detection,” IEEE Transactions on Geoscience and Remote Sensing, vol. 63, 2025, doi: 10.1109/TGRS.2025.3612417.

[2] Z. Cui, J. Yuan, H. Xu, Y. Wei, and Z. Ding*, “RTL-Net: Real-Time Lightweight Urban Traffic Object Detection Algorithm,” Complex & Intelligent Systems, vol. 11, no. 7, 2025, doi: 10.1007/s40747-025-01875-z.

[3] Z. Cui, J. Yuan, H. Wang, Y. Li, C. Du, and Z. Ding*, “Draw with Thought: Unleashing Multimodal Reasoning for Scientific Diagram Generation,” in Proc. 33rd ACM Int. Conf. Multimedia (MM ’25), pp. 5050–5059, 2025.

[4] W. Yu, C. Li, Z. Ding*, et al., “A Class of Two-Dimensional Offset-Boostable Chaotic Maps,” Chaos, Solitons & Fractals, vol. 195, 2025, doi: 10.1016/j.chaos.2025.116361.

[5] Z. Ding, W. Song, J. Xu, W. Cheng, and S. Zhan, “A Deep-Learning-Based Low-Cost Micro-Leakage Measurement System for Industrial Applications,” IEEE/ASME Transactions on Mechatronics, vol. 29, no. 1, pp. 119–130, Feb. 2024, doi: 10.1109/TMECH.2023.3272797.

[6] Z. Ding, Z. Yin, W. Song, W. Cheng, J. Xu, and S. Zhan, “Simulations of Bubble Formation and Oscillation Behavior in Micro-Leakage Measurement System,” IEEE Transactions on Instrumentation and Measurement, vol. 72, pp. 1–9, 2023, Art. no. 7502709, doi: 10.1109/TIM.2023.3261926.

[7] Z. Ding, W. Song, and S. Zhan, “A Measurement System for the Tightness of Sealed Vessels Based on Machine Vision Using Deep Learning Algorithm,” IEEE Transactions on Instrumentation and Measurement, vol. 71, pp. 1–15, 2022, Art. no. 5007115, doi: 10.1109/TIM.2022.3158989.

[8] Z. Yin, Z. Ding*, X. Ma, et al., “Molecular Dynamics Simulations of Single Water Nanodroplet Impinging Vertically on Curved Copper Substrate,” Microgravity Science and Technology, vol. 31, pp. 749–757, 2019.