head

Bio

I will join Visa Research as a full-time research scientist in Fall 2022.

I am currently a sixth-year CS Ph.D. student in Big Data and Social Computing (BDSC) Lab at University of Illinois Chicago. My advisor is Prof. Philip S. Yu. Before joining UIC, I received my B.E. from Beijing University of Posts and Telecommunications in 2017. My research interests are Graph Mining, Fraud Detection, and Secure Machine Learning.

Curriculum VitaeTwitterLinkedInSafeGraphGoogle ScholarGithubPyGOD

News

  • [09/2022] Our node outlier detection benchmark is accepted by NeurIPS 2022.
  • [09/2022] My blog about GNN-based anomaly detection is featured on TigerGraph Blog.
  • [08/2022] Our graph attack&defense survey is accepted by IEEE TKDE.
  • [08/2022] Give a talk about GNN-based Anomaly Detection at Novartis Data Science Seminar.
  • [08/2022] Give a talk about GNN-based Financial Fraud Detection at Machine Learning in Finance Workshop@KDD'22.
  • [08/2022] One paper is accepted by CIKM 2022.
  • [08/2022] Be invited to serve as a PC member for AAAI 2023.
  • [06/2022] Release a benchmark for node outlier detection on graphs.
  • [06/2022] Be invited to serve as a reviewer for LoG 2022.
  • [06/2022] Be invited to serve as a reviewer for NeurIPS 2022.
  • [05/2022] Be invited to serve as a PC member for ASONAM 2022.
  • [05/2022] Be invited to serve as a PC member for CIKM 2022.
  • [04/2022] Be invited to serve as a PC member for CySoc@ICWSM 2022.
  • [04/2022] Release a Python Library for Graph Outlier Detection (PyGOD).
  • [04/2022] Received the Papers with Code Contributor Award from Papers With Code.
  • [03/2022] Be invited to serve as the Video Conference Chair for TheWebConference 2022.
  • [03/2022] Give a talk at IIT for event and misinformation detection on Twitter [Slides PDF].
  • [02/2022] I will join VISA Research as a full-time staff research scientist this summer.
  • [12/2021] Our fraud dataset has become a benchmark on PaperWithCode.
  • [12/2021] Be invited to serve as a PC member for CONSTRAINT@ACL 2022.
  • [11/2021] Be invited to serve as a PC member for KDD 2022.
  • [11/2021] Be invited to serve as the Whova Chair for WSDM 2022, e-meet you in 02/2022!
  • [10/2021] One paper collaborated with Grab has been accepted by IEEE BigData.
  • [10/2021] Our Cross-lingual COVID-19 fake news dataset has been accepted by ICDMW.
  • [10/2021] Give a talk about GNN-based fraud detection at Datafun Summit.
  • [09/2021] Be invited to serve as a PC member for SDM 2022.
  • [08/2021] The CARE-GNN model proposed by us has been integrated with DGL.
  • [08/2021] Be invited to serve as a PC member for WSDM 2022.
  • [07/2021] Be invited to serve as a PC member for IJCAI 2022-2024.
  • [06/2021] Start the summer intern at Snap Research.
  • [05/2021] Our fake news dataset has been added to PyG and DGL as a graph classification benchmark.
  • [05/2021] Our GNN-based Fraud Detection toolbox DGFraud-TF2 has upgraded to TensorFlow 2.0.
  • [05/2021] Give two talks at F5 Security and Grab Inc. (Slides PDF).
  • [05/2021] Be invited to serve as a PC member for ASONAM 2021.
  • [05/2021] Release a GNN-based Fake News Detection Repo with two news propagation graph datasets.
  • [04/2021] Two papers are accepted by SIGIR 2021.
  • [04/2021] One paper is accepted by IEEE TKDE.
  • [01/2021] One paper is accepted by The Web Conference 2021.
  • [12/2020] I will join the CSS Team @Snap Research as a research intern in Summer 2021.
  • [10/2020] Be invited to serve as PC members for AAAI-21 and IJCAI-21.
  • [08/2020] We release an Unsupervised Graph-based Fraud Detection Toolbox.
  • [07/2020] One paper is accepted by CIKM 2020.
  • [05/2020] One paper is accepted by KDD 2020.
  • [05/2020] We release a Deep Graph-based Fraud Detection Toolbox.
  • [04/2020] One paper is accepted by SIGIR 2020.
  • [07/2019] One paper was accepted to ASONAM 2019.
  • [01/2019] Move my personal website from Wordpress to Github.
  • [01/2019] Give a talk about graph based spammer detection at Tencent.
  • [05/2018] Start summer intern at the Search and Recommendation Group of Huawei Noah’s Ark Lab.
  • [02/2018] Publish a dataset with Chinese O2O service Wechat lucky package sharing log.
  • [10/2017] An article is published on IEEE Access.
  • [08/2017] Start my Ph.D. at the University of Illinois at Chicago.
  • [06/2017] Graduate from BUPT and QMUL with the Beijing Excellent Graduate prize.
  • [04/2017] Decide to join the BDSC Lab at UIC under the supervision of Prof. Philip Yu.
  • [03/2017] Join D-Lab in the Institute for Data Science of Tsinghua University as a research volunteer.
  • [09/2016] A paper is accepted by the 2nd workshop of EMGIS in 2016 ACM SIGSPATIAL.
  • [08/2016] Attend KDD 2016 at San Francisco.
  • [07/2016] Start summer intern at UIC Big Data and Social Computing Lab.
  • [06/2016] Attend ICDSC 2016 in Changsha, China.
  • Talks and Blogs

  • [Blog] Graph Neural Network-based Graph Outlier Detection: A Brief Introduction at TigerGraph Blog.
  • [Talk] GNN-based Anomaly Detection: from Research to Application at Novartis Data Science Seminar.
  • [Talk] Leveraging GNNs for Financial Fraud Detection: Practices and Challenges at KDD 2022, Washington DC.
  • [Talk] Mining Twitter for Social Event and Misinformation Detection at IIT, Chicago.
  • [Talk] GNN-based Fraud Detection: from Research to Application at Datafun Summit.
  • [Talk] Robust Fraud Detection against Adversarial Fraudsters at F5 Security and Grab Inc.
  • [Blog] Tackling Fake Downloads in Mobile App Markets at Medium.
  • [Talk] An Introduction to Graph-based Spam Review Detection. at Tencent.
  • Preprints

  • PyGOD: A Python Library for Graph Outlier Detection.
  •    Kay Liu*, Yingtong Dou*, Yue Zhao* et al.
       Preprint. Apr. 2022.
       [Paper][Code][BibTeX]

    Selected Publications

  • Benchmarking Node Outlier Detection on Graphs.
  •    Kay Liu*, Yingtong Dou*, Yue Zhao* et al.
       NeurIPS 2022.
       [Paper][Code][BibTeX]

  • Automating DBSCAN via Deep Reinforcement Learning.
  •    Ruitong Zhang, Hao Peng, Yingtong Dou, Jia Wu, Qingyun Sun, Jingyi Zhang, Philip S. Yu.
       ACM CIKM. 2022.
       [Paper][Code][BibTeX]

  • Adversarial Attack and Defense on Graph Data: A Survey.
  •    Lichao Sun, Yingtong Dou, Carl Yang, Kai Zhang, Ji Wang, Philip S. Yu, Lifang He, Bo Li.
       IEEE TKDE. 2022.
       [Paper][Paper List][BibTeX]

  • User Preference-aware Fake News Detection.
  •    Yingtong Dou, Kai Shu, Congying Xia, Philip S. Yu, Lichao Sun.
       ACM SIGIR. 2021. (Trending New Datasets for 2021)
       [Paper][Code][Slides][Video][PyG Example][DGL Example][Data][Chinese Blog][BibTeX]

  • Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters.
  •    Yingtong Dou, Zhiwei Liu, Li Sun, Yutong Deng, Hao Peng, Philip S. Yu.
       ACM CIKM. 2020. (Top 10 Influential Papers at CIKM’20)
       [Paper][Code][Slides][DGL Example][BibTeX]

  • Robust Spammer Detection by Nash Reinforcement Learning.
  •    Yingtong Dou, Guixiang Ma, Philip S. Yu, Sihong Xie.
       ACM SIGKDD. 2020.
       [Paper][Code][Slides][Video][Chinese Blog][BibTeX]

    (All publications)