Dr. Shengyong Ding

Associate professor, doctoral supervisor/master supervisor 

Email：syding@cityu.edu.mo

Tel: (853)85902428

Office address: Room N401A, Choi Kai Yau Building, City University of Macau (Taipa)

Academic Qualifications

2015: PhD in Computer Applications, Sun Yat-sen University, China

2008: Master of Applied Mathematics, Sun Yat-sen University, China

2001: Bachelor of Information Management, University of Science and Technology of China, China

Research Interests

·  Spatial Intelligence: Integrating SLAM, multimodal large language models, long-term 4D spatial memory, active perception, and embodied reasoning to investigate how intelligent agents can continuously understand environmental changes, connect natural language with the real 3D world, and make autonomous decisions and take actions under uncertainty and safety constraints.

·  Multimodal Large Language Models: Focusing on multimodal understanding, reasoning, and generation, including multimodal question answering, high-quality QA generation, and controllable 3D content generation driven by text, images, and spatial information, advancing models from multisource perception toward reliable understanding, deep reasoning, and 3D world construction.

·  Applied Research: Integrating spatial intelligence and multimodal large language models to investigate language-guided robot navigation, semantic mapping, active exploration and task planning in dynamic real-world environments, multi-agent modeling and simulation of social systems, and natural human–robot interaction, thereby advancing the application of these technologies in healthcare, education, and related domains.

Research & Publications

Refereed Journal Articles

Li, Z., Ding, S., & Li, S. (2026). DiFRa: A unified framework for harmonizing semantic diversity and factual consistency in question-answer generation. Findings of the Association for Computational Linguistics: ACL 2026, 29857–29875.

Wang, X., Ma, X., Ding, S., & Wong, D. F. (2025). Evaluation of text-to-image generation from a creativity perspective. Findings of the Association for Computational Linguistics: EMNLP 2025, 481–493.

Wang, X., Ma, X., Ding, S., Chao, L. S., & Wong, D. F. (2025). Mitigating object hallucination through assembled chain-of-thought reasoning. Natural Language Processing and Chinese Computing (NLPCC 2025), 16103, 48–61

Liu, Y., Liu, X., Ding, S., & Yang, Z. (2025). Robustly solving PnL problem using Clifford tori. Pattern Recognit., 166, 111659.

Xiao, Zelin & Lin, Hongxin & Li, Renjie & Geng, Lishuai & Chao, Hongyang & Ding, Shengyong. (2020). Endowing Deep 3d Models With Rotation Invariance Based On Principal Component Analysis. 1-6. 10.1109/ICME46284.2020.9102947.

Lin, Hongxin & Xiao, Zelin & Tan, Yang & Chao, Hongyang & Ding, Shengyong. (2019). Justlookup: One Millisecond Deep Feature Extraction for Point Clouds By Lookup Tables. 326-331. 10.1109/ICME.2019.00064.

Tan, Yang & Lin, Hongxin & Xiao, Zelin & Ding, Shengyong & Chao, Hongyang. (2019). Face Recognition from Sequential Sparse 3D Data via Deep Registration. 1-8. 10.1109/ICB45273.2019.8987284.

Wang, Guangrun & Lin, Liang & Ding, Shengyong & Li, Ya & Wang, Qing. (2016). DARI: Distance Metric and Representation Integration for Person Verification. Proceedings of the AAAI Conference on Artificial Intelligence. 30. 10.1609/aaai.v30i1.10462.

Ding, Shengyong & Lin, Liang & Wang, Guangrun & Chao, Hongyang. J(2015). Deep Feature Learning with Relative Distance Comparison for Person Re-identification. Pattern Recognition. 48. 10.1016/j.patcog.2015.04.005.

Academic Awards

2018 Pattern Recognition Best Paper