Ph.D. Student
Brickyard Suit, 699 S Mill Ave, Tempe, AZ 85281

Google Scholar DBLP


News and Highlights

[11/2019] One paper is accepted in ICWSM'20

[9/2019] Fires in the Amazon: Arizona researchers determine what’s true, what’s not, an interview with Arizona PBS Cronkite News on AI and fake news [video].

[9/2019] AI Squares Off Against Fake News. -- feature news about KDD'19 tutorial.

[8/2019] Clickbait Secrets Exposed! Humans and AI team up to improve clickbait detection.

[8/2019] Invited talk (remotely participating) at Microsoft AI on Learning with Weak Supervision.

[8/2019] Invited to serve as a PC member for AAAI'20.

[7/2019] Our book Detecting Fake News on Social Media is online.

[6/2019] Received the student travel award for KDD'19.

[6/2019] Two papers are accepted in ASONAM'19.

[6/2019] Invited talk at Microsoft Research AI Power Lunch talk series on fake news detection.

[4/2019] One paper on "Explainable Fake News Detection" is accepted in KDD'19.

[4/2019] Our tutorial on "Fake News Research: Theories, Detection Strategies, and Open Problems" is accepted in KDD'19. See you in Anchorage, Alaska!

[3/2019] One paper on exploiting emojis for sarcasm detection got accepted at SBP.

[3/2019] Invited to serve as PC member in ASONAM'19.

[2/2019] Our WSDM paper on fake news detection is nicely featured in the morning paper


Research Experience

[Aug. 2015 - Present]
Research Assistant at DMML, Arizona State University, Tempe, AZ, USA.

[May 2019 - August 2019]
Research Intern at Microsoft AI Research, Redmond, WA, USA.

[May 2018 - August 2018]
Research Intern at Yahoo! Research, Sunnyvale, CA, USA.

[Jul. 2014 - June 2015]
Research visiting student at ICT, Chinese Academy of Sciences, Beijing, China.

[Mar. 2012 - Sept. 2013]
Research Intern at HP Labs China, Beijing, China.

I am a final year PhD student in the Department of Computer Science and Engineering at Arizona State University, Tempe, AZ. I am a research assistant at the Data Mining and Machine Learning Lab (DMML). My advisor is Professor Huan Liu. My research lies in artificial intelligence, machine learning, data mining, and social computing. My research is highly interdisciplinary and I closely collaborate with social scientists and computational journalists. Recently, I am actively working on leveraging weak social supervision for disinformation and fake news detection on social media.

I am looking for a tenure-track faculty position in machine learning, data science, artificial intelligence, social computing, and related fields. [CV]
Detecting Fake News on Social Media          
     Detecting Fake News on Social Media

     Morgan & Claypool Publishers, 2019

Co-Instructor/Teaching Assistant in Fall'19    CSE 472 Social Media Mining
Office hours: Tuesday 12:00pm - 1:00pm BYE 221


Selected Publications [Full List]

  • Hierarchical Propagation Networks for Fake News Detection: Investigation and Exploitation. [PDF]
    Kai Shu, Deepak Mahudeswaran, Suhang Wang, and Huan Liu.
    Proceedings of 14th the International AAAI Conference on Web and Social Media (ICWSM 2020)
  • Exploring Correlation Network for Cheating Detection. [PDF]
    Ping Luo, Kai Shu, Junjie Wu, Li Wan, and Yong Tan.
    ACM TIST, 2019.
  • Using Synthetic Clickbaits to Improve Prediction and Distinguish between Bot-Generated and Human-Written Headlines. [PDF]
    Thai Le, Kai Shu, Maria D. Molina, Dongwon Lee, S. Shyam Sundar, and Huan Liu.
    Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2019)
    Media coverage: [Newswise]
  • dEFEND: Explainable Fake News Detection. [PDF][Code]
    Kai Shu, Limeng Cui, Suhang Wang, Dongwon Lee, and Huan Liu.
    Proceedings of 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2019)
    Media coverage: [Techxplore Today]
  • Unsupervised Fake News Detection on Social Media: A Generative Approach. [PDF][Code]
    Shuo Yang, Kai Shu, Suhang Wang, Renjie Gu, Fan Wu, and Huan Liu.
    Proceedings of 33rd AAAI Conference on Artificial Intelligence (AAAI 2019) .
  • Beyond News Content: The Role of Social Context for Fake News Detection.
    Kai Shu, Suhang Wang, and Huan Liu.
    Proceedings of 12th ACM International Conference on Web Search and Data Mining (WSDM 2019).
    Media coverage: [KDnuggets] [The Morning Paper]
  • FakeNewsTracker: A Tool for Fake News Collection, Detection, and Visualization. [PDF]Poster][Demo]
    Kai Shu, Deepak Mahudeswaran, and Huan Liu.
    Computational and Mathematical Organization Theory, 2019 (CMOT 2019). Best of SBP
  • Studying Fake News via Network Analysis: Detection and Mitigation. [PDF][A Course Blog from Cornell University]
    Kai Shu, H. Russell Bernard, and Huan Liu.
    Lecture Notes in Social Network (LNSN), Springer Press, 2018.
  • Deep Headline Generation for Clickbait Detection. [PDF][Slides]
    Kai Shu, Suhang Wang, Thai Le, Dongwon Lee, and Huan Liu.
    The 2018 IEEE International Conference on Data Mining (ICDM 2018) (Regular Paper)
  • Multimodal Fusion of Brain Networks with Longitudinal Couplings. [PDF]
    Wen Zhang, Kai Shu, Suhang Wang, Huan Liu, and Yalin Wang.
    21th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2018).
  • Securing Social Media User Data - An Adversarial Approach. [PDF]
    Ghazaleh Beigi, Kai Shu, Yanchao Zhang, and Huan Liu.
    29th ACM Conference on Hypertext and Social Media (HT 2018).
  • CrossFire: Cross Media Joint Friend and Item Recommendations. [PDF][Slides][Poster]
    Kai Shu, Suhang Wang, Jiliang Tang, Yilin Wang, and Huan Liu.
    Proceedings of 11th ACM International Conference on Web Search and Data Mining (WSDM 2018).
  • 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.
    Proceedings of 26th International World Wide Web Conference (WWW 2017).
  • User Identity Linkage across Online Social Networks: A Review. [PDF]
    Kai Shu, Suhang Wang, Jiliang Tang, Reza Zafarani, and Huan Liu.
    SIGKDD Explorations, 2016.
  • Multi-Label Informed Feature Selection. [PDF]
    Ling Jian, Jundong Li, Kai Shu, and Huan Liu.
    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.
    Proceedings of the 23rd ACM International Conference on Information and Knowledge Management (CIKM 2014).