Kai Shu  

Ph.D. Student

Department of Computer Science and Engineering
Arizona State University

Brickyard Suit, 699 S Mill Ave, Tempe, AZ 85281


[Biography] [Research Interests] [News] [Publications] [Research Experiences] [Services] [Awards]

Biography

Kai is a PhD student in the Department of Computer Science and Engineering at Arizona State University, Tempe, AZ. He also works as a research assistant at the Data Mining and Machine Learning Lab (DMML). His advisor is Professor Huan Liu. Before that, he obtained his BE in 2012 and MS in 2015 both in CS from Chongqing University, Chongqing, China. He also worked as a research visiting student in the Institute of Computing Technology, Chinese Academy of Sciences during his MS degree.


Research Interests

His research interests include data mining and machine learning, especially innovative real-world applications.


News

    [10/10/2017] Our survey about fake news detection on social media is featured in KDNuggets!


Publication List

    Journal Papers
  • Fake News Detection on Social Media: A Data Mining Perspective. [PDF]
    Kai Shu, Amy Sliva, Suhang Wang, Jiliang Tang and Huan Liu.
    In SIGKDD Explorations, 2017.
  • User Identity Linkage across Online Social Netwroks: A Review. [PDF]
    Kai Shu, Suhang Wang, Jiliang Tang, Reza Zafarani and Huan Liu.
    In SIGKDD Explorations, 2016.
    Conference Papers
  • Personalized Privacy-Preserving Social Recommendation. [PDF]
    Xuying Meng, Suhang Wang, Kai Shu, Jundong Li, Bo Chen, Huan Liu and Yujun Zhang.
    In Proceedings of 32nd AAAI Conference on Artificial Intelligence (AAAI 2018).
  • CrossFire: Cross Media Joint Friend and Item Recommendations. [PDF]
    Kai Shu, Suhang Wang, Jiliang Tang, Yilin Wang and Huan Liu.
    In Proceedings of 11th ACM International Conference on Web Search and Data Mining (WSDM 2018).
  • Cross-Platform Emoji Interpretation: Analysis, a Solution, and Applications. [PDF]
    Fred Morstatter, Kai Shu, Suhang Wang and Huan Liu.
    preprint in arXiv.
  • What Your Images Reveal: Exploiting Visual Contents for Point-of-Interest Recommendation. [PDF]
    Suhang Wang, Yilin Wang, Jiliang Tang, Kai Shu, Suhas Ranganath and Huan Liu.
    In Proceedings of 26th International World Wide Web Conference (WWW 2017).
  • Multi-Label Informed Feature Selection. [PDF]
    Ling Jian, Jundong Li, Kai Shu and Huan Liu.
    In Proceedings of 25th International Joint Conference on Artificial Intelligence (IJCAI 2016).
  • Deal or deceit: detecting cheating in distribution channels. [PDF][slides]
    Kai Shu, Ping Luo, Li Wan, Peifeng Yin and Linpeng Tang.
    In Proceedings of the 23rd ACM International Conference on Information and Knowledge Management (CIKM 2014).
  • Sequences modeling and analysis based on complex network. [PDF]
    Li Wan, Kai Shu and Yu Guo.
    In Communications and Information Processing. Springer Berlin Heidelberg, pages 246-252, 2012.

Research Experiences

  • Research Intern at HP Labs China, Beijing, China. (Mar. 2012 - Sept. 2013)

Services

  • Conference Reviewer: BigData'16,17
  • Journal Reviewer: TKDE'17, Neurocomputing'17, JOCS'17
  • External Reviewer: AAAI'18, CIKM'17, IJCAI'16, 17, WSDM'17, ASONAM'16,17, RecSys'16, ICWSM'16

Awards

  • CIDSE Doctoral Fellowship Award, Arizona State University, Aug. 2015

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