Weixiang Shao (邵蔚翔)

I joined Google (Mountain View, CA) in August 2016.

Before that, I was pursing my Ph.D degree in Department of Computer Science, University of Illinois at Chicago advised by Philip S. Yu. I worked in the Big Data and Social Computing (BDSC) Lab focusing on unsupervised learning, multi-view learning and social network analysis.

Before my Ph.D. degree, I received my B.E. degree from Software Institute, Nanjing University and my M.S. degree in Statistics from Department of MSCS, University of Illinois at Chicago.


  1. Huayi Li, Geli Fei, Shuai Wang, Bing Liu, Weixiang Shao, Arjun Mukherjee, Jidong Shao. Bimodal Distribution and Co-Bursting in Review Spam Detection. In proceedings of the 26th International Conference on World Wide Web (WWW 2017). [paper, bib]

  2. Chun-Ta Lu, Lifang He, Weixiang Shao, Bokai Cao and Philip S. Yu. Multilinear Factorization Machines for Multi-Task Multi-View Learning. In proceedings of 2017 ACM International Conference on Web Search and Data Mining. (WSDM 2017). [paper, bib]

  3. Weixiang Shao, Lifang He, Chun-Ta Lu, and Philip S. Yu. Online Multi-view Clustering with Incomplete Views. In proceedings of 2016 IEEE International Conference on Big Data. (Bigdata 2016). [paper,slides code, bib]

  4. Xiaokai Wei, Bokai Cao, Weixiang Shao, Chun-Ta Lu, and Philip S. Yu. Community Detection with Partially Observable Links and Node Attributes. In proceedings of 2016 IEEE International Conference on Big Data. (Bigdata 2016). [paper, code, bib]

  5. Weixiang Shao, Lifang He, Chun-Ta Lu, Xiaokai Wei, and Philip S. Yu. Online Unsupervised Multi-view Feature Selection. In proceedings of the 2016 International Conference on Data Mining. (ICDM 2016). [paper, slides code, bib]

  6. Weixiang Shao, Jiawei Zhang, Lifang He and Philip S. Yu. Multi-Source Multi-View Clustering via Discrepancy Penalty. In proceedings of the 2016 International Joint Conference on Neural Networks. (IJCNN 2016). [paper, bib]

  7. Chun-Ta Lu, Sihong Xie, Weixiang Shao, Lifang He and Philip S. Yu. Item Recommendation for Emerging Online Businesses. In proceedings of the 25th International Joint Conference on Artificial Intelligence (IJCAI 2016). [paper, slides, poster bib]

  8. Sihong Xie, Qingbo Hu, Weixiang Shao, Jingyuan Zhang, Jing Gao, Wei Fan, and Philip S. Yu. Effective Crowd Expertise Modeling via Cross Domain Sparsity and Uncertainty Reduction. In proceedings of the 16th SIAM International Conference on Data Mining (SDM 2016). [paper, bib]

  9. Jiawei Zhang, Weixiang Shao, Senzhang Wang, Xiangnan Kong, Philip S. Yu. PNA: Partial Network Alignment with Generic Stable Matching. In proceedings of 2015 IEEE International Conference on Information Reuse and Integration (IRI 2015). [paper, bib, slides]

  10. Weixiang Shao, Lifang He, and Philip S. Yu. Multiple Incomplete Views Clustering via Weighted Nonnegative Matrix Factorization with L2,1 Regularization. In proceedings of The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery (ECML PKDD 2015) [paper, bib, code].

  11. Weixiang Shao, Lifang He, Philip S. Yu. Clustering on Multi-source Incomplete Data via Tensor Modeling and Factorization. In proceedings of the 19th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2015). [paper, bib]

  12. Weixiang Shao, Clive E. Adams, Aaron M. Cohen, John M. Davis, Marian S. McDonagh, Sujata Thakurta, Philip S. Yu, and Neil R. Smalheiser. Aggregator: a machine learning approach to identifying MEDLINE articles that derive from the same underlying clinical trial. Methods 74 (2015): 65-70. [paper, bib]

  13. Neil R. Smalheiser, Weixiang Shao, and Philip S. Yu. Nuggets: Findings Shared in Multiple Clinical Case Reports. Journal of the Medical Library Association (JMLA) 103.4 (2015): 171-176. [paper, bib]

  14. Weixiang Shao, Xiaoxiao Shi, and Philip S. Yu. Clustering on multiple incomplete datasets via collective kernel learning. In proceedings of the IEEE 13th International Conference on Data Mining (ICDM 2013) [paper, bib, code].

  15. Weixiang Shao. Unsupervised learning from multi-view data. Ph.D. Thesis (University of Illinois at Chicago, 2016).

Contact me


software.shao[AT]gmail.com                View Weixiang Shao's profile on LinkedIn