I am currently a Ph.D. candidate at the School of Computer Science, Fudan University (2023–present), under the supervision of Prof. Weidong Yang, and I am expected to graduate in 2027. Prior to this, I received my M.S. degree from Guangzhou University in June 2023, advised by Prof. Xiaofang Zhou.

🔍 Research Interests

My research interests focus on spatio-temporal data mining and time-series modeling, with applications in intelligent transportation systems (ITS) and beyond. My current work spans regional-, road-, and lane-level traffic prediction, aiming to achieve high-accuracy forecasting to support downstream tasks such as routing, signal control, and tidal lane management. I also explore the integration of large-scale pre-trained models and large language models (LLMs) to improve the scalability, generalization, and multimodal capabilities of traffic forecasting. Specifically, my work covers:

• Lane-level traffic prediction: Fine-grained modeling and inference of lane-level traffic states for real-world applications.
• Spatio-temporal fine-grained forecasting: Multi-granularity and cross-scale sequence modeling for accurate traffic prediction.
• Lightweight traffic pre-training models: Designing efficient and transferable spatio-temporal pre-training frameworks.
• LLMs for intelligent transportation: Investigating the potential of LLMs in traffic forecasting, decision-making, and multimodal applications.

I warmly welcome collaborations with researchers interested in spatio-temporal data mining, intelligent transportation, time-series modeling, and large models.

For more information, please visit my academic profiles: Google Scholar · DBLP.

💥 News

• [May 2025] Our paper on fine-grained traffic inference has been accepted to KDD 2025.
• [Feb 2025] Our work on the lane-level traffic prediction benchmark and baselines has been accepted to TKDE.
• [Jul 2024] Our paper McgVAE on lane-level traffic prediction has been accepted to CIKM 2024.
• [Mar 2024] Our paper ST-ABC on lane-level traffic prediction has been accepted to ICDE 2024.

📑 Selected Publications

2025

• Shuhao Li, Weidong Yang, Yue Cui, Xiaoxing Liu, Lingkai Meng, Lipeng Ma, Fan Zhang
  Fine-Grained Traffic Inference from Road to Lane via Spatio-Temporal Graph Node Generation.
  SIGKDD CCF A

• Shuhao Li, Yue Cui, Jingyi Xu, Libin Li, Lingkai Meng, Weidong Yang, Fan Zhang, Xiaofang Zhou
  Unifying Lane-Level Traffic Prediction From a Graph Structural Perspective: Benchmark and Baseline.
  IEEE Trans. Knowl. Data Eng. (TKDE) 37(9): 5699–5718 (2025)
  CCF A, SCI Q1

2024

• Shuhao Li, Yue Cui, Jingyi Xu, Jing Zhao, Fan Zhang, Weidong Yang, Xiaofang Zhou
  Seeing the Forest for the Trees: Road-Level Insights Assisted Lane-Level Traffic Prediction.
  CIKM CCF B

• Shuhao Li, Yue Cui, Libin Li, Weidong Yang, Fan Zhang, Xiaofang Zhou
  ST-ABC: Spatio-Temporal Attention-Based Convolutional Network for Multi-Scale Lane-Level Traffic Prediction.
  ICDE CCF A

2023

• Shuhao Li, Yue Cui, Yan Zhao, Weidong Yang, Ruiyuan Zhang, Xiaofang Zhou
  ST-MoE: Spatio-Temporal Mixture-of-Experts for Debiasing in Traffic Prediction.
  CIKM CCF B

• Yue Cui, Shuhao Li, Wenjin Deng, Zhaokun Zhang, Jing Zhao, Kai Zheng, Xiaofang Zhou
  ROI-demand Traffic Prediction: A Pre-train, Query and Fine-tune Framework.
  ICDE CCF A

📖 Academic Services

Conference PC Member

• 2026: KDD, AAAI
• 2025: NeurIPS, KDD, WWW, ICML, ICLR
• 2024: NeurIPS

Invited Journal Reviewer

• 2025: TKDE, TEENG
• 2024: TKDE, Neural Networks, TCCN

External Reviewer

• 2024: ICDE, CIKM, DASFAA, ICASSP
• 2023: ICDM

🏆 Honors & Awards

• CSC National Scholarship for Study Abroad (2025)
• Fudan–Huawei Scholarship (2024)
• First-Class Academic Scholarship, Fudan University (2023)
• GZU–Jinhang Technology Scholarship (2022)

👀 Visitors