Yu Shi

I am a fourth-year Ph.D. student in Computer Science at University of Illinois at Urbana-Champaign under the supervision of Professor Jiawei Han. My research interest mainly lies in data mining and machine learning with a focus on interpreting and modeling typed network/graph data.

Before joining UIUC, I obtained my bachelor's degree from Hua Loo-Keng Talent Program in Mathematics at University of Science and Technology of China. I have also spent summers interning at LinkedIn, Snap Research, and Facebook.

Email  /  CV  /  LinkedIn

Publications
  • Yu Shi*, Qi Zhu*, Fang Guo, Chao Zhang, Jiawei Han. Easing Embedding Learning by Comprehensive Transcription of Heterogeneous Information Networks. In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2018. (Research track)
  • [Paper] [Code & Data] [Video]
  • Yu Shi, Huan Gui, Qi Zhu, Lance Kaplan, and Jiawei Han. AspEm: Embedding Learning by Aspects in Heterogeneous Information Networks. In Proceedings of the 2018 SIAM International Conference on Data Mining (SDM), 2018.
  • [Paper & Supp File] [Code & Data] [Slides]
  • Yu Shi, Po-Wei Chan, Honglei Zhuang, Huan Gui, and Jiawei Han. PReP: Path-Based Relevance from a Probabilistic Perspective in Heterogeneous Information Networks. In Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2017. (Research track oral presentation)
  • [Paper] [Code & Data] [Slides] [Video]
  • Yu Shi*, Myunghwan Kim*, Shaunak Chatterjee, Mitul Tiwari, Souvik Ghosh, and Romer Rosales. Dynamics of Large Multi-View Social Networks: Synergy, Cannibalization and Cross-View Interplay. In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2016. (Research track)
  • [Paper] [Video]
  • Yuchen Li, Zhengzhi Lou, Yu Shi, Jiawei Han. Temporal Motifs in Heterogeneous Information Networks. In Proceedings of the 14th International Workshop on Mining and Learning with Graphs (MLG), co-located with KDD, 2018.
  • [Paper]
  • Wei Cheng, Jingchao Ni, Kai Zhang, Haifeng Chen, Guofei Jiang, Yu Shi, Xiang Zhang, and Wei Wang. Ranking Causal Anomalies for System Fault Diagnosis via Temporal and Dynamical Analysis on Vanishing Correlations. Transactions on Knowledge Discovery from Data (TKDD), 2017. (Best papers of KDD'16)
  • [Paper]
  • Wei Cheng, Yu Shi, and Wei Wang. Sparse Regression Models for Unraveling Group and Individual Associations in eQTL Mapping. BMC Bioinformatics, 2016.
  • [Paper]
  • Wei Cheng, Yu Shi, Xiang Zhang, and Wei Wang. Fast and Robust Group-Wise eQTL Mapping Using Sparse Graphical Models. BMC Bioinformatics, 2015.
  • [Paper]
  • Wei Cheng, Xiang Zhang, Zhishan Guo, Yu Shi, and Wei Wang. Graph Regularized Dual Lasso for Robust eQTL Mapping. In Proceedings of the 21st Annual International Conference on Intelligent Systems for Molecular Biology (ISMB), 2014.
  • [Paper]
        Work in submission:
  • Yu Shi, Fangqiu Han, Xinran He, Carl Yang, Luo Jie, and Jiawei Han. mvn2vec: Preservation and Collaboration in Multi-View Network Embedding. arXiv:1801.06597.
  • [Preprint]
(* indicates equal contribution.)
Teaching

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