Chao Wang 王超

中国科学技术大学人工智能与数据科学学院, 预聘副教授, 博导
Email: wangchaoai@ustc.edu.cn

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王超，现为中国科学技术大学人工智能与数据科学学院预聘副教授，博导。2016年于中科大少年班学院获学士学位，2022年于中科大计算机学院获博士学位（博士导师熊辉、陈恩红教授），2024年从广州市香港科大霍英东研究院、香港科技大学（广州）博士后出站（合作导师王炜教授）。

主要研究方向为数据挖掘、大模型应用、图神经网络、推荐系统等领域。近年来承担多项科研项目，包括国家自然科学基金青年基金C类、安徽省自然科学基金青年基金C类、认知智能全国重点实验室开放课题、CCF-阿里1688源宝合作基金、国家博士后面上基金等，作为项目子课题负责人参与新一代人工智能重大科技专项1项。在相关领域国际重要期刊及会议发表论文40余篇，已授权专利4项。曾获得中国计算机学会CCF优秀博士学位论文激励计划（CCF优博，每年仅10人）、《中国科学：信息科学》2022年度热点论文、翟光龙学者基金等荣誉。

Wang Chao is currently a Tenure-track Associate Professor and Ph.D. Supervisor at the School of Artificial Intelligence and Data Science, University of Science and Technology of China. He received his bachelor’s degree from the School of the Gifted Young, USTC, in 2016, and his Ph.D. degree from the School of Computer Science and Technology, USTC, in 2022, under the supervision of Professors Hui Xiong and Enhong Chen. In 2024, he completed his postdoctoral research at the HKUST Fok Ying Tung Research Institute in Guangzhou and the Hong Kong University of Science and Technology (Guangzhou), under the mentorship of Professor Wei Wang.

His research interests mainly include data mining, applications of large language models, graph neural networks, recommender systems, and related areas. In recent years, he has led multiple research projects, including the Young Scientists Fund Category C of the National Natural Science Foundation of China, the Young Scientists Fund Category C of the Natural Science Foundation of Anhui Province, an open project of the National Key Laboratory of Cognitive Intelligence, the CCF-Alibaba 1688 Yuanbao Collaborative Research Fund, and the General Program of the China Postdoctoral Science Foundation. He has also participated as a sub-project leader in one major science and technology project under the New Generation Artificial Intelligence initiative. He has published more than 40 papers in leading international journals and conferences in related fields and has been granted four patents. His honors include the CCF Outstanding Doctoral Dissertation Incentive Program of the China Computer Federation, awarded to only 10 recipients each year; the 2022 Hot Paper Award of SCIENTIA SINICA Informationis; and the Zhaiguanglong Scholar Fund.


代表性论著

  1. Jin Li, Yaming Guo, Shenghao Gao, Xinlong Chen, Zuhao Xu, Ying Sun, Chao Wang, Hui Xiong. Low-cost Full Fine-tuning: Learning What to Update for LLMs. Forty-third International Conference on Machine Learning (ICML-2026), 2026, accepted. (CCF A)

  2. Zheng Gong, Ying Sun, Chao Wang, Xiaohui Huo, Ping Li, Yi Zheng, Zhefeng Wang. Representation-Aware Modularity: Efficient Cross-Task Generalization for LLMs. 35th International Joint Conference on Artificial Intelligence (IJCAI-2026), 2026, accepted. (CCF B)

  3. Jiaming Leng, Yunying Bi, Chuan Qin, Zhenya Huang, Bing Yin, Haojie Ren, Yanyong Zhang*, Chao Wang*. TransLLM: A Unified Multi-Task Large Language Model for Urban Transportation via Learnable Prompting. The 64th Annual Meeting of the Association for Computational Linguistics (ACL-2026), 2026, accepted. (CCF A)

  4. Xi Chen, Chuan Qin, Jinpeng Li, Shasha Hu, Chao Wang, Hengshu Zhu, Hui Xiong. GenDis: Generative-Discriminative Dual-View Co-Training for Generalized Category Discovery. The 64th Annual Meeting of the Association for Computational Linguistics (ACL-2026), 2026, accepted. (CCF A)

  5. YanShen Yi, Chao Wang*, Ying Sun, Qi Zhang, Xunpeng Huang, Hui Xiong*. Enhancing Fund Recommendations with Multi-round Feedback-based Reinforcement Learning. Frontiers of Computer Science (FCS), 2026, accepted. (CCF B)

  6. Peng Du, YongWen Ren, Hui Liao, Hao Li, Hui Xiong, Chao Wang*. FLAME: Improving Legal Case Retrieval through Factor-aware Graph Modeling and Mixture-of-Experts. Frontiers of Computer Science (FCS), 2026, accepted. (CCF B)

  7. Yunchu Bai, Chao Wang*, Ying Sun, Chuan Qin, Wei Wu, Hui Xiong*. Graph-based Prompt Learning with Mixture of Experts for Multi-task Corporate Profiling. ACM Transactions on Knowledge Discovery from Data, (ACM TKDD), 2026, accepted. (CCF B)

  8. Xi Chen, Chuan Qin, Ziqi Wang, Shasha Hu, Chao Wang, Hengshu Zhu, Hui Xiong. Beyond the Known: An Unknown-Aware Large Language Model for Open-Set Text Classification. The Fourteenth International Conference on Learning Representations (ICLR-2026), 2026, accepted. (CCF A)

  9. Ranxu Zhang, Junjie Meng, Ying Sun, Ziqi Xu, Bing Yin, Hao Li, Yanyong Zhang and Chao Wang*. MCLMR: A Model-Agnostic Causal Learning Framework for Multi-Behavior Recommendation. Proceedings of the 33rd World Wide Web Conference (WWW-2026), 2026, accepted. (CCF A)

  10. Jiaming Leng, Chao Wang*, Qi Zhang, Jianyao Hu, Leilei Ding, Bing Yin, Yanyong Zhang*. Decoding Citywide Electric Vehicle Charging Dynamics with Multi-View Heterogeneous Spatio-temporal Graph Networks. Frontiers of Computer Science (FCS), 2026, accepted. (CCF B)

  11. Lingfeng Liu, Yixin Song, Dazhong Shen, Bing Yin, Hao Li, Yanyong Zhang, Chao Wang*. Rethinking Popularity Bias in Collaborative Filtering via Analytical Vector Decomposition. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD-2026), 2026, accepted. (CCF A)

  12. Yongwen Ren, Chao Wang*, Peng Du, Chuan Qin, Dazhong Shen, Hui Xiong*. Enhancing Conversational Recommender Systems with Tree-Structured Knowledge and Pretrained Language Models. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI-2026), 2026, accepted. (CCF A)

  13. Chao Wang#*, Yixin Song#, Jinhui Ye, Chuan Qin, Dazhong Shen, Lingfeng Liu, Xiang Wang, Yanyong Zhang. FACE: A general Framework for Mapping Collaborative Filtering Embeddings into LLM Tokens. The Thirty-ninth Annual Conference on Neural Information Processing Systems, (NeurIPS-2025), 2025, accepted. (CCF A)

  14. Wei Wu, Zhuoshi Pan, Kun Fu, Chao Wang, Liyi Chen, Yunchu Bai, Tianfu Wang, Zheng Wang, Hui Xiong. TokenSelect: Efficient Long-Context Inference and Length Extrapolation for LLMs via Dynamic Token-Level KV Cache Selection. The 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP -2025), 2025, accepted. (CCF B)

  15. Wei Wu, Chao Wang*, Liyi Chen, Mingze Yin, Yiheng Zhu, Kun Fu, Jieping Ye, Hui Xiong, Zheng Wang. Structure-Enhanced Protein Instruction Tuning: Towards General-Purpose Protein Understanding with LLMs. ACM SIGKDD Conference on Knowledge Discovery and Data Mining, (KDD-2025), 2025, accepted. (CCF A)

  16. Hanzhe Li, Dazhong Shen, Chao Wang, Yuting Liu and Jingjing Gu. Can LLMs Enhance Fairness in Recommendation Systems? A Data Augmentation Approach. The 48th International ACM SIGIR Conference on Research and Development in Information Retrieval, (SIGIR-2025), 2025, accepted. (CCF A)

  17. Leilei Ding, Zhipeng Tang, Le Zhang, Dazhong Shen, Chao Wang, Ziyang Tao, Jingbo Zhou, Yanyong Zhang, Hui Xiong. Killing two birds with one stone: A Spatio-Temporal Prompt for the Inductive Spatio-Temporal Extrapolation. The 30th International Conference on Database Systems for Advanced Applications (DASFAA-2025), 2025, accepted. (CCF B)

  18. Shengzhe Zhang, Liyi Chen, Dazhong Shen, Chao Wang*, Hui Xiong*. Hierarchical Time-Aware Mixture of Experts for Multi-Modal Sequential Recommendation. Proceedings of the 32nd World Wide Web Conference (WWW-2025), 2025, accepted. (CCF A)

  19. Haoran Xin, Ying Sun, Chao Wang, Hui Xiong. LLMCDSR: Enhancing Cross-Domain Sequential Recommendation with Large Language Models. ACM Transactions on Information Systems (ACM TOIS), 2025, accepted. (CCF A)

  20. Xi Chen, Chuan Qin, Chuyu Fang, Chao Wang, Chen Zhu, Fuzhen Zhuang, Hengshu Zhu, Hui Xiong. Job-SDF: A Multi-Granularity Dataset for Job Skill Demand Forecasting and Benchmarking. The Thirty-eight Conference on Neural Information Processing Systems, (NeurIPS-2024), 2024, accepted. (CCF A)

  21. Tianfu Wang, Liwei Deng, Chao Wang, Jianxun Lian, Yue Yan, Nicholas Jing Yuan, Qi Zhang, Hui Xiong. COMET: NFT Price Prediction with Wallet Profiling. ACM SIGKDD Conference on Knowledge Discovery and Data Mining, (KDD-2024), 2024, accepted. (CCF A)

  22. Leilei Ding, Dazhong Shen, Chao Wang*, Tianfu Wang, Le Zhang, Yanyong Zhang*. DGR: A General Graph Desmoothing Framework for Recommendation via Global and Local Perspectives. The 33rd International Joint Conference on Artificial Intelligence, (IJCAI-2024), 2024, accepted. (CCF A)

  23. Tianfu Wang, Qilin Fan, Chao Wang*, Long Yang, Leilei Ding, Nicholas Jing Yuan, Hui Xiong*. FlagVNE: A Flexible and Generalizable Reinforcement Learning Framework for Network Resource Allocation. The 33rd International Joint Conference on Artificial Intelligence, (IJCAI-2024), 2024, accepted. (CCF A)

  24. Xi Chen, Chuan Qin, Zhigaoyuan Wang, Yihang Cheng, Chao Wang, Hengshu Zhu, Hui Xiong. Pre-DyGAE: Pre-training Enhanced Dynamic Graph Autoencoder for Occupational Skill Demand Forecasting. The 33rd International Joint Conference on Artificial Intelligence, (IJCAI-2024), 2024, accepted. (CCF A)

  25. Wei Wu, Chao Wang*, Dazhong Shen, Chuan Qin, Liyi Chen, Hui Xiong*. AFDGCF: Adaptive Feature De-correlation Graph Collaborative Filtering for Recommendations. The 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, (SIGIR-2024), 2024, accepted. (CCF A)

  26. Yunqin Zhu, Chao Wang*, Qi Zhang, Hui Xiong*. Graph Signal Diffusion Model for Collaborative Filtering. The 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, (SIGIR-2024), 2024, accepted. (CCF A)

  27. Shuyao Wang, Yongduo Sui, Chao Wang, Hui Xiong. Unleashing the Power of Knowledge Graph for Recommendation via Invariant Learning. Proceedings of the 31st World Wide Web Conference (WWW-2024), 2024. (CCF A)

  28. Shengzhe Zhang, Liyi Chen, Chao Wang, Shuangli Li, Hui Xiong. Temporal Graph Contrastive Learning for Sequential Recommendation. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI-2024), 2024, accepted. (CCF A)

  29. Shasha Hu, Chao Wang*, Chuan Qin, Hengshu Zhu, and Hui Xiong*. Super-node Generation for GNN-based Recommender Systems: Enhancing Distant Node Integration via Graph Coarsening. The 29th International Conference on Database Systems for Advanced Applications (DASFAA-2024), Gifu, Japan, accepted, 2024. (CCF B)

  30. Chao Wang, Hengshu Zhu, Chen Zhu, Chuan Qin, Hui Xiong. SetRank: A Setwise Bayesian Approach for Collaborative Ranking in Recommender System. ACM Transactions on Information Systems (ACM TOIS), 2023, accepted. (CCF A)

  31. Siyuan Hao, Le Dai, Le Zhang, Shengming Zhang, Chao Wang, Chuan Qin, and Hui Xiong. Hybrid Heterogeneous Graph Neural Networks for Fund Performance Prediction. In Proceedings of the 16th International Conference on Knowledge Science, Engineering and Management (KSEM-2023), accepted, Guangzhou, China, 2023. (CCF C)

  32. Zhi Zheng, Chao Wang, Tong Xu, Dazhong Shen, Penggang Qin, Xiangyu Zhao, Baoxing Huai, Xian Wu, and Enhong Chen. Interaction-aware drug package recommendation via policy gradient. ACM Transactions on Information Systems (ACM TOIS), 2022, 41(1): 1-32. (CCF A)

  33. Chao Wang, Hengshu Zhu, Peng Wang, Chen Zhu, Xi Zhang, Enhong Chen, Hui Xiong. Personalized and Explainable Employee Training Course Recommendations: A Bayesian Variational Approach. ACM Transactions on Information Systems (ACM TOIS), 2022, 40(4): 1-32. (CCF A)

  34. Chao Wang, Hengshu Zhu, Qiming Hao, Keli Xiao, Hui Xiong. Variable Interval Time Sequence Modeling for Career Trajectory Prediction: Deep Collaborative Perspective. In Proceedings of the 28th World Wide Web Conference (WWW-2021), Ljubljana, 2021. (CCF A)

  35. Dazhong Shen, Chuan Qin, Chao Wang, Zheng Dong, Hengshu Zhu, and Hui Xiong. Topic Modeling Revisited: A Document Graph-based Neural Network Perspective. The 35th Conference on Neural Information Processing Systems (NeurIPS-2021), Virtual Conference, Dec. 6-14th 2021. (CCF A)

  36. Zhi Zheng, Chao Wang, Tong Xu, Dazhong Shen, Penggang Qin, Baoxing Huai, Tongzhu Liu, Enhong Chen. Drug Package Recommendation via Interaction-aware Graph Induction. The 30th International World Wide Web Conference (WWW-2021), Ljubljana, Slovenia, April 19-23 2021. (CCF A)

  37. Dazhong Shen, Chuan Qin, Chao Wang, Hengshu Zhu, Enhong Chen, Hui Xiong. Regularizing Variational Autoencoder with Diversity and Uncertainty Awareness. In Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI-2021), 2021. (CCF A)

  38. Miao Chen, Chao Wang, Chuan Qin, Tong Xu, Jianhui Ma, Enhong Chen, Hui Xiong. A Trend-aware Investment Target Recommendation System with Heterogeneous Graph. In Proceedings of the 2021 International Joint Conference on Neural Networks (IJCNN-2021), Shenzhen, China, 2021. (CCF C)

  39. Chao Wang, Hengshu Zhu, Chen Zhu, Chuan Qin, Hui Xiong. SetRank: A setwise Bayesian approach for collaborative ranking from implicit feedback. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI-2020). 2020, 34(04): 6127-6136. (CCF A)

  40. Chao Wang, Hengshu Zhu, Chen Zhu, Xi Zhang, Enhong Chen, Hui Xiong. Personalized Employee Training Course Recommendation with Career Development Awareness. Proceedings of The Web Conference 2020 (WWW-2020). 2020: 1648-1659. (CCF A)

  41. Chuan Qin, Hengshu Zhu, Fuzhen Zhuang, Qingyu Guo, Qi Zhang, Le Zhang, Chao Wang, Enhong Chen, Hui Xiong. A survey on knowledge graph-based recommender systems. Scientia Sinica Informationis, 2020, 50(7): 937-956. [秦川, 祝恒书, 庄福振, 郭庆宇, 张琦, 张乐, 王超, 陈恩红, 熊辉, 基于知识图谱的推荐系统研究综述, 中国科学: 信息科学, 2020] (CCF A 中文核心)

  42. Chengqiang Lu, Qi Liu, Chao Wang, Zhenya Huang, Peize Lin, Lixin He. Molecular property prediction: A multilevel quantum interactions modeling perspective. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI-2019). 2019, 33(01): 1052-1060. (CCF A)

  43. Xiaoqing Huang, Qi Liu, Chao Wang, Haoyu Han, Jianhui Ma, Enhong Chen. Constructing Educational Concept Maps with Multiple Relationships from Multi-source Data. 2019 IEEE International Conference on Data Mining (ICDM-2019). IEEE, 2019: 1108-1113. (CCF B)

  44. Chao Wang, Qi Liu, Runze Wu, Enhong Chen, Chuanren Liu, Xunpeng Huang, Zhenya Huang. Confidence-aware matrix factorization for recommender systems. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI-2018). 2018, 32(1). (CCF A)

  45. Runlong Yu, Yunzhou Zhang, Yuyang Ye, Le Wu, Chao Wang, Qi Liu, Enhong Chen. Multiple pairwise ranking with implicit feedback. Proceedings of the 27th ACM International Conference on Information and Knowledge Management (CIKM-2018). 2018: 1727-1730. (CCF B)

  46. Chao Wang, Qi Liu, Enhong Chen, Zhenya Huang, Tianyu Zhu, Yu Su, Guoping Hu. The Rapid Calculation Method of DINA Model for Large Scale Cognitive Diagnosis. [王超，刘淇，陈恩红，黄振亚，朱天宇，苏喻，胡国平，面向大规模认知诊断的DINA模型快速计算方法研究, 电子学报，46(5):1047-1055，2018]. (CCF A 中文核心)