张玉东 Yudong Zhang Ph.D. Data Intelligence Laboratory Suzhou Institute for Advanced Research School of Artificial Intelligence and Data Science University of Science and Technology of China Supervisors: Professor Yang Wang (Vice Dean of the School of Software Engineering), Professor Jie Wang (Vice Dean of the School of the Gifted Young) [News] I will be joining the Suzhou Institute for Advanced Research at USTC as a faculty member this year. Interested students (Master’s/PhD applicants or interns) are welcome to get in touch!

Biography

Currently, I am a member of the Data Intelligence Laboratory led by Prof. Yang Wang, focusing on cutting-edge research in AI, and maintaining close collaborations with researchers from leading institutions worldwide, including Rutgers, NUS, NTU, Tsinghua, Shanghai AI Laboratory, Zhongguancun Academy, and HKUST (GZ). I obtained my Ph.D. degree from the School of Artificial Intelligence and Data Science at USTC in 2025, after which I joined the faculty at the Suzhou Institute for Advanced Research.

Education

• 2020.09 ~ 2025.06
  Ph.D. degree: Data Science, School of Artificial Intelligence and Data Science, University of Science and Technology of China.

• 2016.09 ~ 2020.06
  B.Sc. degree: Electronic Science and Technology, School of Electronic Science and Engineering, University of Electronic Science and Technology of China.

Research Interests

• Spatial-Temporal Data Mining, Time Series Analysis, Multi-Agent System, and Large Models.

• Urban Computing, Decision Intelligence, and AI4Science.

Publications

Journal Papers:

• Yudong Zhang, Xu Wang*, Pengkun Wang, Binwu Wang, Zhengyang Zhou, Yang Wang*, Modeling Spatio-Temporal Mobility Across Data Silos via Personalized Federated Learning, IEEE Transactions on Mobile Computing, (TMC), 2024. (CCF-A, JCR-Q1, IF=7.7)

• Yudong Zhang, Xu Wang*, Zhaoyang Sun, Pengkun Wang, Binwu Wang, Limin Li, Yang Wang*, Meta Koopman decomposition for time series forecasting under temporal distribution shifts, Advanced Engineering Informatics, (AEI), 2024. (CCF-B, JCR-Q1, IF=8.0)

• Yudong Zhang, Pengkun Wang, Binwu Wang, Xu Wang, Zhe Zhao, Zhengyang Zhou, Lei Bai*, Yang Wang*, Adaptive and Interactive Multi-Level Spatio-Temporal Network for Traffic Forecasting, IEEE Transactions on Intelligent Transportation Systems, (TITS), 2024. (CCF-B, JCR-Q1, IF=7.9)

• Li-Min Li, Bin-Wu Wang*, Xu Wang, Peng-Kun Wang, Yu-Dong Zhang, Yang Wang*, Face Anti-spoofing with Unknown Attacks: A Comprehensive Feature Extraction and Representation Perspective, Journal of Computer Science and Technology, (JCST), 2024. (CCF-B)

• Binwu Wang, Pengkun Wang*, Yudong Zhang, Xu Wang, Zhengyang Zhou, Yang Wang*, Condition-Guided Urban Traffic Co-Prediction With Multiple Sparse Surveillance Data, IEEE Transactions on Vehicular Technology, (TVT), 2024. (JCR-Q1, IF=6.1).

• Kun Wang, Yuxuan Liang*, Xinglin Li, Guohao Li, Bernard Ghanem, Roger Zimmermann, Zhengyang Zhou, Huahui Yi, Yudong Zhang, Yang Wang*, Brave the Wind and the Waves: Discovering Robust and Generalizable Graph Lottery Tickets, IEEE Transactions on Pattern Analysis and Machine Intelligence, (TPAMI), 2023. (CCF-A, JCR-Q1, IF=20.8)

• Xu Wang, Pengkun Wang, Binwu Wang, Yudong Zhang, Zhengyang Zhou, Lei Bai, Yang Wang*, Latent Gaussian Processes based Graph Learning for Urban Traffic Prediction, IEEE Transactions on Vehicular Technology, (TVT), 2023. (JCR-Q1, IF=6.1)

• Binwu Wang, Yudong Zhang, Jiahao Shi, Pengkun Wang, Xu Wang, Lei Bai*, Yang Wang*, Knowledge Expansion and Consolidation for Continual Traffic Prediction with Expanding Graphs, IEEE Transactions on Intelligent Transportation Systems, (TITS), 2023. (CCF-B, JCR-Q1, IF=7.9)

Conference Papers:

• Yudong Zhang, Zhaoyang Sun, Xu Wang*, Xuan Yu, Kai Wang, Yang Wang*, Time-Frequency Disentanglement Boosted Pre-Training: A Universal Spatio-Temporal Modeling Framework, The 34th International Joint Conference on Artificial Intelligence, (IJCAI), 2025. (CCF-A)

• Yudong Zhang, Xu Wang*, Xuan Yu, Zhengyang Zhou, Xing Xu, Lei Bai, Yang Wang*, DiffODE: Neural ODE with Differentiable Hidden State for Irregular Time Series Analysis, The 41st IEEE International Conference on Data Engineering, (ICDE), 2025. (CCF-A)

• Yudong Zhang, Xuan Yu, Xu Wang*, Zhaoyang Sun, Chen Zhang, Pengkun Wang, Yang Wang*, COFlowNet: Conservative Constraints on Flows Enable High-Quality Candidate Generation, The Thirteenth International Conference on Learning Representations, (ICLR), 2025. (CORE-A*, THU-A)

• Yudong Zhang, Xu Wang*, Xuan Yu, Kuo Yang, Zhengyang Zhou, Yang Wang*, FedSTG: Breaking through Spatio-Temporal Data Silos with Federated Graph Learning, The ACM Web Conference 2025 (short paper, formerly known as the International World Wide Web Conference), (WWW), 2025.

• Yudong Zhang, Xu Wang*, Xuan Yu, Kuo Yang, Zhengyang Zhou, Yang Wang*, Do We Really Need GCNs in Traffic Forecasting? A Graph-Less Pure-MLP Architecture, The ACM Web Conference 2025 (short paper, formerly known as the International World Wide Web Conference), (WWW), 2025.

• Yudong Zhang, Xu Wang*, Xuan Yu, Zhaoyang Sun, Kai Wang, Yang Wang*, Drawing Informative Gradients from Sources: A One-stage Transfer Learning Framework for Cross-city Spatiotemporal Forecasting, The 39th Annual AAAI Conference on Artificial Intelligence, (AAAI), 2025. (CCF-A, Oral Presentation)

• Zhaoyang Sun, Yudong Zhang*, Xuan Yu, Kai Wang, Binwu Wang, Yang Wang*, Xu Wang, Time-Space-Interlaced Spatiotemporal Graph Forecasting via Two-Stage Summarized Attention, The 50th IEEE International Conference on Acoustics, Speech, and Signal Processing, (ICASSP), 2025. (CCF-B)

• Ziyan Wang, Yudong Zhang, Pengkun Wang, Xu Wang*, Yang Wang*, Embedding Enhanced MLP Enables Simple and Extensible Spatiotemporal Forecasting, The 50th IEEE International Conference on Acoustics, Speech, and Signal Processing, (ICASSP), 2025. (CCF-B)

• Binwu Wang, Jiaming Ma, Pengkun Wang, Xu Wang, Yudong Zhang, Zhengyang Zhou, Yang Wang*, STONE: A Spatio-temporal OOD Learning Framework Kills Both Spatial and Temporal Shifts, The 30th SIGKDD Conference on Knowledge Discovery and Data Mining, (SIGKDD), 2024. (CCF-A)

• Binwu Wang, Pengkun Wang*, Wei Xu, Xu Wang, Yudong Zhang, Kun Wang, Yang Wang*, Kill Two Birds with One Stone: Rethinking Data Augmentation for Deep Long-tailed Learning, The Twelfth International Conference on Learning Representations, (ICLR), 2024. (CORE-A*, THU-A)

• Binwu Wang, Pengkun Wang*, Yudong Zhang, Xu Wang, Zhengyang Zhou, Lei Bai, Yang Wang*, Towards Dynamic Spatial-Temporal Graph Learning: A Decoupled Perspective, The 38th Annual AAAI Conference on Artificial Intelligence, (AAAI), 2024. (CCF-A)

• Zhe Zhao, Pengkun Wang*, Haibin Wen, Yudong Zhang, Zhengyang Zhou, Yang Wang*, A Twist for Graph Classification: Optimizing Causal Information Flow in Graph Neural Networks, The 38th Annual AAAI Conference on Artificial Intelligence, (AAAI), 2024. (CCF-A)

• Xu Wang, Pengfei Gu, Yudong Zhang, Binwu Wang, Pengkun Wang, Yang Wang*, Gradient Reactivation Enhanced Causal Attention for Out-Of-Distribution Generalizable Graph Classification, The 49th IEEE International Conference on Acoustics, Speech, and Signal Processing, (ICASSP), 2024. (CCF-B)

• Zhe Zhao, Pengkun Wang*, Haibin Wen, Yudong Zhang, Binwu Wang, Yang Wang*, Graph Networks Stand Strong: Enhancing Robustness via Stability Constraints, The 49th IEEE International Conference on Acoustics, Speech, and Signal Processing, (ICASSP), 2024. (CCF-B)

• Binwu Wang, Yudong Zhang, Xu Wang, Pengkun Wang, Zhengyang Zhou, Lei Bai*, Yang Wang*, Pattern Expansion and Consolidation on Evolving Graphs for Continual Traffic Prediction, The 29th SIGKDD Conference on Knowledge Discovery and Data Mining, (SIGKDD), 2023. (CCF-A)

• Xu Wang, Hongbo Zhang, Pengkun Wang, Yudong Zhang, Binwu Wang, Zhengyang Zhou, Yang Wang*, An Observed Value Consistent Diffusion Model for Imputing Missing Values in Multivariate Time Series, The 29th SIGKDD Conference on Knowledge Discovery and Data Mining, (SIGKDD), 2023. (CCF-A)

• Zhengyang Zhou, Qihe Huang, Kuo Yang, Kun Wang, Xu Wang, Yudong Zhang, Yuxuan Liang, Yang Wang*, Maintaining the Status Quo: Capturing Invariant Relations for OOD Spatiotemporal Learning, The 29th SIGKDD Conference on Knowledge Discovery and Data Mining, (SIGKDD), 2023. (CCF-A)

• Yudong Zhang, Wei Lu, Xu Wang, Pengkun Wang*, Yang Wang*, Pondering About Task Spatial Misalignment: Classification-Localization Equilibrated Object Detection, The 48th IEEE International Conference on Acoustics, Speech, and Signal Processing, (ICASSP), 2023. (CCF-B)

• Binwu Wang, Yudong Zhang, Pengkun Wang, Xu Wang, Lei Bai*, Yang Wang*, A Knowledge-Driven Memory System for Traffic Flow Prediction, The 28th International Conference on Database Systems for Advanced Applications, (DASFAA), 2023. (CCF-B)

• Pengkun Wang, Xu Wang, Binwu Wang, Yudong Zhang, Lei Bai*, Yang Wang*, Long-Tailed Time Series Classification via Feature Space Rebalancing, The 28th International Conference on Database Systems for Advanced Applications, (DASFAA), 2023. (CCF-B)

• Pengkun Wang, Xu Wang, Binwu Wang, Yudong Zhang, Lei Bai*, Yang Wang*, Countering Modal Redundancy and Heterogeneity: A Self-Correcting Multimodal Fusion, The 22nd IEEE International Conference on Data Mining, (ICDM), 2022. (CORE-A*, CCF-B)

• Yudong Zhang, Binwu Wang, Ziyang Shan, Zhengyang Zhou*, Yang Wang*, CMT-Net: A Mutual Transition Aware Framework for Taxicab Pick-ups and Drop-offs Co-Prediction, The 15th ACM International Conference on Web Search and Data Mining, (WSDM), 2022. (CORE-A*, THU-A, CCF-B)

(The authors with * are the corresponding authors.)

Academic Services

• Invited Program Committee Member/Reviewer for Conferences:
  ICML (2025), ICLR (2025), NeurIPS (2025, 2024), IJCAI (2025), TheWebConf (2025), ACM MM (2025, 2024), AISTATS (2025), CHI (2025), ECAI (2025, 2023), ICWSM (2025), ICASSP (2025, 2024), ICME (2025, 2024), Globecom (2024), ECML-PKDD (2023), CogSci (2025), IJCNN (2025).

• Invited Reviewer for Journals:
  IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Mobile Computing, IEEE Transactions on Intelligent Transportation Systems, IEEE Transactions on Emerging Topics in Computational Intelligence, IEEE Internet of Things Journal, Information Fusion, Pattern Recognition, Expert Systems with Applications, Neural Networks, Knowledge-Based Systems, Applied Soft Computing, Neurocomputing, Scientific Reports, Machine Learning.

Teaching Services

• 2025: Serve as a TA for Theory of Algorithm (Spring 2025), School of Software Engineering, USTC.

• 2024: Serve as a TA for Design and Analysis of Algorithms (Autumn 2024), School of Software Engineering, USTC.

• 2024: Serve as a TA for Design and Analysis of Algorithms (Autumn 2024), School of Computer Science and Technology, USTC.

• 2024: Serve as a TA for Big Data Analysis (Spring 2024), School of Software Engineering, USTC.

• 2024: Serve as a TA for Theory of Algorithm (Spring 2024), School of Software Engineering, USTC.

• 2023: Serve as a TA for Data Warehouse and Data Mining (Autumn 2023), School of Software Engineering, USTC.

• 2023: Serve as a TA for Design and Analysis of Algorithms (Autumn 2023), School of Computer Science and Technology, USTC.

• 2022: Serve as a TA for Design and Analysis of Algorithms (Autumn 2022), School of Computer Science and Technology, USTC.

• 2022: Serve as a TA for Distributed and Cloud Computing (Spring 2022), School of Software Engineering, USTC.

• 2021: Serve as a TA for Natural Language Processing (Autumn 2021), School of Software Engineering, USTC.

• 2021: Serve as a TA for EDA Technology (Autumn 2021), School of Software Engineering, USTC.

Co-Supervised Students

• Ph.D. Students: Zhaoyang Sun (from University of Science and Technology of China)

• Master Students: Rui Zhu (from Tianjin University), Di Lu (from Jilin University), Wenjun Fang (from China University of Geosciences (Wuhan)), Yang Cheng (from Hangzhou Dianzi University), Feng Niu (from National University of Defense Technology), Wenxuan Rao (from Shanghai Jiao Tong University)

Correspondence

Email: zyd2020@mail.ustc.edu.cn

Laboratory: Office 302, Biomed. Eng. Building, Ruoshui Road Campus, Suzhou Institute for Advanced Research, USTC

Address: 99 Ruoshui Road, Suzhou Industrial Park, Suzhou, Jiangsu, 215123, China
(江苏省苏州市苏州工业园区若水路99号, 中国科学技术大学苏州高等研究院生物医学工程楼, 215123.)

Related Links

Prof. Yang Wang (USTC)

Dr. Lei Bai (Shanghai AI Lab)

Dr. Zhengyang Zhou (USTC)

Dr. Pengkun Wang (USTC)

Dr. Xu Wang (USTC)

Dr. Binwu Wang (USTC)

Dr. Kun Wang (NTU)