王 超
E-mail：wangchaoai@ustc.tsg211.com
主要研究方向：数据挖掘、大模型应用、图神经网络、推荐系统
王超，现为图书馆VIP人工智能与数据科学学院预聘副教授。2016年于图书馆VIP少年班学院获理科学士学位，2022年于图书馆VIP计算机学院获工学博士学位，博士导师为熊辉教授和陈恩红教授，2024年于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，博士后合作导师为王炜教授。
近年来，主持国家博士后面上基金1项、广州市博士后科研项目1项、南沙区博士后科研项目1项，作为项目骨干参与科技部重点研发项目1项。在相关领域国际重要期刊及会议发表论文20余篇，其中以第一作者及通讯作者身份发表CCF推荐的A类期刊和会议论文10余篇，已公开专利7项，与华为、讯飞、百度等企业长期合作，参与制定中国人工智能产业发展联盟团体标准1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（每年4篇）、中科院院长优秀奖等荣誉。
主要论著：
1. Xi Chen, Chuan Qin, Chuyu Fang,Chao Wang, Chen Zhu, Fuzhen Zhuang, Hengshu Zhu, Hui Xiong. Job-SDF: AMulti-Granularity Dataset for Job Skill Demand Forecasting and Benchmarking.The Thirty-eight Conference on Neural Information Processing Systems, (NeurIPS-2024),2024, accepted. (CCF A)
2. Tianfu Wang, Liwei Deng, ChaoWang, Jianxun Lian, Yue Yan, Nicholas Jing Yuan, Qi Zhang, Hui Xiong. COMET:NFT Price Prediction with Wallet Profiling. ACM SIGKDD Conference on KnowledgeDiscovery and Data Mining, (KDD-2024), 2024, accepted. (CCF A)
3. Leilei Ding, Dazhong Shen, ChaoWang*, Tianfu Wang, Le Zhang, Yanyong Zhang*. DGR: A General Graph DesmoothingFramework for Recommendation via Global and Local Perspectives. The 33rdInternational Joint Conference on Artificial Intelligence, (IJCAI-2024), 2024,accepted. (CCF A)
4. Tianfu Wang, Qilin Fan, ChaoWang*, Long Yang, Leilei Ding, Nicholas Jing Yuan, Hui Xiong*. FlagVNE: AFlexible and Generalizable Reinforcement Learning Framework for NetworkResource Allocation. The 33rd International Joint Conference on ArtificialIntelligence, (IJCAI-2024), 2024, accepted. (CCF A)
5. Xi Chen, Chuan Qin, ZhigaoyuanWang, Yihang Cheng, Chao Wang, Hengshu Zhu, Hui Xiong. Pre-DyGAE: Pre-trainingEnhanced Dynamic Graph Autoencoder for Occupational Skill Demand Forecasting.The 33rd International Joint Conference on Artificial Intelligence,(IJCAI-2024), 2024, accepted. (CCF A)
6. Wei Wu, Chao Wang*, DazhongShen, Chuan Qin, Liyi Chen, Hui Xiong*. AFDGCF: Adaptive Feature De-correlationGraph Collaborative Filtering for Recommendations. The 47th International ACMSIGIR Conference on Research and Development in Information Retrieval,(SIGIR-2024), 2024, accepted. (CCF A)
7. Yunqin Zhu, Chao Wang*, QiZhang, Hui Xiong*. Graph Signal Diffusion Model for Collaborative Filtering.The 47th International ACM SIGIR Conference on Research and Development inInformation Retrieval, (SIGIR-2024), 2024, accepted. (CCF A)
8. Shuyao Wang, Yongduo Sui, ChaoWang, Hui Xiong. Unleashing the Power of Knowledge Graph for Recommendation viaInvariant Learning. Proceedings of the 31st World Wide Web Conference(WWW-2024), 2024. (CCF A)
9. Shengzhe Zhang, Liyi Chen, ChaoWang, Shuangli Li, Hui Xiong. Temporal Graph Contrastive Learning forSequential Recommendation. Proceedings of the AAAI Conference on ArtificialIntelligence (AAAI-2024), 2024, accepted. (CCF A)
10. Shasha Hu, Chao Wang*, ChuanQin, Hengshu Zhu, and Hui Xiong*. Super-node Generation for GNN-basedRecommender 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)
11. Chao Wang, Hengshu Zhu, ChenZhu, Chuan Qin, Hui Xiong. SetRank: A Setwise Bayesian Approach forCollaborative Ranking in Recommender System. ACM Transactions on InformationSystems (ACM TOIS), 2023, accepted. (CCF A)
12. Siyuan Hao, Le Dai, Le Zhang,Shengming Zhang, Chao Wang, Chuan Qin, and Hui Xiong. Hybrid HeterogeneousGraph Neural Networks for Fund Performance Prediction. In Proceedings of the16th International Conference on Knowledge Science, Engineering and Management(KSEM-2023), accepted, Guangzhou, China, 2023. (CCF C)
13. Zhi Zheng, Chao Wang, Tong Xu,Dazhong Shen, Penggang Qin, Xiangyu Zhao, Baoxing Huai, Xian Wu, and EnhongChen. Interaction-aware drug package recommendation via policy gradient. ACMTransactions on Information Systems (ACM TOIS), 2022, 41(1): 1-32. (CCF A)
14. Chao Wang, Hengshu Zhu, PengWang, Chen Zhu, Xi Zhang, Enhong Chen, Hui Xiong. Personalized and ExplainableEmployee Training Course Recommendations: A Bayesian Variational Approach. ACMTransactions on Information Systems (ACM TOIS), 2022, 40(4): 1-32. (CCF A)
15. Chao Wang, Hengshu Zhu, QimingHao, Keli Xiao, Hui Xiong. Variable Interval Time Sequence Modeling for CareerTrajectory Prediction: Deep Collaborative Perspective. In Proceedings of the28th World Wide Web Conference (WWW-2021), Ljubljana, 2021. (CCF A)
16. Dazhong Shen, Chuan Qin, ChaoWang, Zheng Dong, Hengshu Zhu, and Hui Xiong. Topic Modeling Revisited: ADocument Graph-based Neural Network Perspective. The 35th Conference on NeuralInformation Processing Systems (NeurIPS-2021), Virtual Conference, Dec. 6-14th2021. (CCF A)
17. Zhi Zheng, Chao Wang, Tong Xu,Dazhong Shen, Penggang Qin, Baoxing Huai, Tongzhu Liu, Enhong Chen. DrugPackage Recommendation via Interaction-aware Graph Induction. The 30thInternational World Wide Web Conference (WWW-2021), Ljubljana, Slovenia, April19-23 2021. (CCF A)
18. Dazhong Shen, Chuan Qin, ChaoWang, Hengshu Zhu, Enhong Chen, Hui Xiong. Regularizing Variational Autoencoderwith Diversity and Uncertainty Awareness. In Proceedings of the 30thInternational Joint Conference on Artificial Intelligence (IJCAI-2021), 2021.(CCF A)
19. Miao Chen, Chao Wang, ChuanQin, Tong Xu, Jianhui Ma, Enhong Chen, Hui Xiong. A Trend-aware InvestmentTarget Recommendation System with Heterogeneous Graph. In Proceedings of the2021 International Joint Conference on Neural Networks (IJCNN-2021), Shenzhen,China, 2021. (CCF C)
20. Chao Wang, Hengshu Zhu, ChenZhu, Chuan Qin, Hui Xiong. SetRank: A setwise Bayesian approach forcollaborative ranking from implicit feedback. Proceedings of the AAAIConference on Artificial Intelligence (AAAI-2020). 2020, 34(04): 6127-6136.(CCF A)
21. Chao Wang, Hengshu Zhu, ChenZhu, Xi Zhang, Enhong Chen, Hui Xiong. Personalized Employee Training CourseRecommendation with Career Development Awareness. Proceedings of The WebConference 2020 (WWW-2020). 2020: 1648-1659. (CCF A)
22. Chuan Qin, Hengshu Zhu, FuzhenZhuang, Qingyu Guo, Qi Zhang, Le Zhang, Chao Wang, Enhong Chen, Hui Xiong. Asurvey on knowledge graph-based recommender systems. Scientia SinicaInformationis, 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)
23. Chengqiang Lu, Qi Liu, ChaoWang, Zhenya Huang, Peize Lin, Lixin He. Molecular property prediction: Amultilevel quantum interactions modeling perspective. Proceedings of the AAAIConference on Artificial Intelligence (AAAI-2019). 2019, 33(01): 1052-1060.(CCF A)
24. Xiaoqing Huang, Qi Liu, ChaoWang, Haoyu Han, Jianhui Ma, Enhong Chen. Constructing Educational Concept Mapswith Multiple Relationships from Multi-source Data. 2019 IEEE InternationalConference on Data Mining (ICDM-2019). IEEE, 2019: 1108-1113. (CCF B)
25. Chao Wang, Qi Liu, Runze Wu,Enhong Chen, Chuanren Liu, Xunpeng Huang, Zhenya Huang. Confidence-aware matrixfactorization for recommender systems. Proceedings of the AAAI Conference onArtificial Intelligence (AAAI-2018). 2018, 32(1). (CCF A)
26. Runlong Yu, Yunzhou Zhang,Yuyang Ye, Le Wu, Chao Wang, Qi Liu, Enhong Chen. Multiple pairwise rankingwith implicit feedback. Proceedings of the 27th ACM International Conference onInformation and Knowledge Management (CIKM-2018). 2018: 1727-1730. (CCF B)
27. Chao Wang, Qi Liu, Enhong Chen,Zhenya Huang, Tianyu Zhu, Yu Su, Guoping Hu. The Rapid Calculation Method ofDINA 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)