团队科研骨干

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宋 骐 特任教授

发布时间:2020-08-06浏览次数:1029


E-Mail:qisong09@ustc.edu.cn


主要研究方向:数据挖掘、知识图谱、图数据等


宋骐,男,19909月生,安徽合肥人,中国科学院技术大学特任教授,海外优青获得者。2012年和2015年于北京航空航天大学分别获得学士与硕士学位,2020年在华盛顿州立大学获得博士学位。2020年加入亚马逊集团担任应用科学家(Applied Scientist),20221月加入中国科学技术大学计算机学院李向阳院长创建的LINKE实验室。主要研究方向为图数据库及图数据挖掘,近年来在数据库及数据挖掘顶级期刊及会议上发表多篇论文,包括TKDESIGMODICDECIKMICDMICLR等,同时担任多个顶级期刊及会议的审稿人。


代表性著作

  1. Qi Song*, Mohammad Hossein Namaki, Peng Lin, and Yinghui Wu, Answering Why-Questions for Subgraph Queries;  IEEE Transactions on Knowledge and Data Engineering(TKDE) (accepted, early access)   

  2. Qi Song, Peng Lin, Hanchao Ma, Yinghui Wu, Explaining Missing Data in Graphs: A Constraint-based Approach; IEEE 36th International Conference on Data Engineering (ICDE), 2021, pp. 1476-1487  

  3. Qi Song*, Yinghui Wu, Peng Lin, Luna Xin Dong, Hui Sun, Mining summaries for knowledge graph search; IEEE Transactions on Knowledge and Data Engineering(TKDE) 30 (10), 1887-1900 

  4. Qi Song#, Mohammad Hossein Namaki#, Yinghui Wu, Answering Why-Questions for Subgraph Queries in Multi-Attributed Graphs; IEEE 35th International Conference on Data Engineering (ICDE), 2019, pp. 40-51

  5. Mohammad Hossein Namaki#, Qi Song#, Yinghui Wu, Shengqi Yang Answering why-questions by exemplars in attributed graphs; Proceedings of the 2019 International Conference on Management of Data (SIGMOD), 2019, pp. 1481-1498

  6. Qi Song, Bo Zong, Yinghui Wu, Lu-An Tang, Hui Zhang, Guofei Jiang, Haifeng Chen, TGNet: Learning to rank nodes in temporal graphs; Proceedings of the 27th ACM International Conference on Information and Knowledge Management (CIKM), 2018, pp. 97-106

  7. Qi Song, Yinghui Wu, Luna Xin Dong,    Mining Summaries for Knowledge Graph Search; IEEE 16th International Conference on Data Mining (ICDM), 2016, pp. 1215-1220

  8. Peng Lin, Qi Song, Yinghui Wu, Jiaxing Pi,    Repairing Entities using Star Constraints in Multirelational Graphs; IEEE International Conference on Data Engineering (ICDE), 2020, pp 229-240

  9. Bo Zong, Qi Song, Martin Renqiang Min, Wei Cheng, Cristian Lumezanu, Daeki Cho, Haifeng Chen, Deep Autoencoding Gaussian Mixture Model for Unsupervised Anomaly Detection. International Conference on Learning Representations(ICLR) 2018

  10. Peng Lin, Qi Song, Jialiang Shen and Yinghui Wu, Discovering Graph Patterns for Fact Checking in Knowledge Graphs; International Conference On Database Systems for Advanced Applications(DASFAA), 2018, pp 783-801

  11. Mohammad Hossein Namaki, Yinghui Wu, Qi Song, Peng Lin, Tingjian Ge, Discovering Temporal Graph Association Rules. ACM International Conference on Information and Knowledge Management (CIKM), 2017, pp. 1697-1706

  12. Peng Lin, Qi Song, Yinghui Wu, Jiaxing Pi, Discovering Patterns for Fact Checking in Knowledge Graphs; Journal of Data and Information Quality(JDIQ), Volume 11 (Issue 3), 2018, Article No. 13.

  13. Wei Cai, Baochun He, Min Hu, Wenyu Zhang, Deqiang Xiao, Hao Yu, Nan Xiang, Jian Yang, Qi Song, Songsheng He, Yaohuan Huang, Wenjie Huang, Fucang Jia, Chi-hua Fang, A radiomics-based Nomogram for the Preoperative Prediction of Posthepatectomy Liver Failure in Patients with Hepatocellular Carcinoma, Surgical Oncology(SO), 2018, Volume 28, 78-85.

  14. Peng Lin, Qi Song, Yinghui Wu, Fact Checking in Knowledge Graphs with Ontological Subgraph Patterns; Data Science and Engineering(DSE, invited), 2018, Volume 3 (Issue 4), 341–358.