Yuxiao Dong
Senior Applied Scientist
Microsoft Research
Redmond, WA 98052
ericdongyx@Gmail


Research Interests

I am a senior applied scientist at Microsoft Research Redmond. My research focuses on social and information networks, data mining, and applied machine learning, with an emphasis on applying computational models to addressing problems in large-scale networked systems, such as Microsoft Academic Graph (MAG), knowledge graph, online social media, and mobile communication.

I received my Ph.D. in Computer Science from University of Notre Dame in 2017. I have been a visiting scholar at Tsinghua University, Army Research Lab, and AMiner.org. More information can be found on my LinkedIn profile.

  1. WWW'19 Tutorial on Network Representation Learning website&slides
  2. KDD'19 Deep Learning Day Co-Chair: The 2019 ACM SIGKDD Deep Learning Day
  3. WWW'19 Workshop on Deep Learning for Graphs and Structured Data Embedding (DL4G-SDE): International Workshop on Deep Learning for Graphs and Structured Data Embedding. Keynotes' slides are avaiable.

  4. Selected Publications

    Problems:
    Venues:

    1. ProNE: Fast and Scalable Network Representation Learning
      Jie Zhang, Yuxiao Dong, Yan Wang, Jie Tang, Ming Ding.
      IJCAI'19 (Proc. of the 28th International Joint Conference on Artificial Intelligence), 2019. Full paper (Oral).
    2. NetSMF: Large-Scale Network Embedding as Sparse Matrix Factorization code slides_jz poster_jz
      Jiezhong Qiu, Yuxiao Dong, Hao Ma, Jian Li, Chi Wang, Kuansan Wang and Jie Tang
      WWW'19 (Proc. of the 2019 Web Conference), 2019. Full paper (Oral).
    3. Neural Tensor Factorization code slides_xian
      Xian Wu, Baoxu Shi,Yuxiao Dong, Chao Huang, Nitesh V. Chawla.
      WSDM'19 (Proc. of the 12th ACM International Conference on Web Search and Data Mining), 2019. Full paper (Oral), 16%.
    4. DeepInf: Social Influence Prediction with Deep Learning code&data video_jz poster_jz
      Jiezhong Qiu, Jian Tang, Hao Ma, Yuxiao Dong, Kuansan Wang, Jie Tang.
      KDD'18 (Proc. of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining), Full paper (poster presentation), 2018.
    5. Network Embedding as Matrix Factorization: Unifying DeepWalk, LINE, PTE, and node2vec. code slides_jz
      Jiezhong Qiu, Yuxiao Dong, Hao Ma, Jian Li, Kuansan Wang, Jie Tang.
      WSDM'18 (Proc. of the 11th ACM International Conference on Web Search and Data Mining), 2018. Full paper (Oral), 16%.
      Featured on Microsoft Research Blog
    6. RESTFul: Resolution-Aware Forecasting of Behavioral Time Series Data. code
      Xian Wu, Baoxu Shi, Yuxiao Dong, Chao Huang, Louis Faust, Nitesh V. Chawla.
      CIKM'18 (Proc. of the 27th ACM International Conference on Information and Knowledge Management), 2018. Full paper, 17% (accepted).
    7. Who will Attend This Event Together? Event Attendance Prediction via Deep LSTM Networks code&data slides_xian
      Xian Wu, Yuxiao Dong, Baoxu Shi, Ananthram Swami, Nitesh V. Chawla.
      SDM'18 (Proc. of the SIAM International Conference on Data Mining), 2018 (accepted).
    8. Computational Lens on Big Social and Information Networks. slides
      Ph.D. dissertation, University of Notre Dame, 2017.
      ACM SIGKDD Doctoral Dissertation Award 2017 Honorable Mention
    9. metapath2vec: Scalable Representation Learning for Heterogeneous Networks. data&code slides poster video bibtex
      Yuxiao Dong, Nitesh V. Chawla, Ananthram Swami.
      KDD'17 (Proc. of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining), 2017. Full Research Paper (Oral), 8.5%.
    10. A Century of Science: Globalization of Scientific Collaborations, Citations, and Innovations. data poster bibtex
      Yuxiao Dong, Hao Ma, Zhihong Shen, Kuansan Wang.
      KDD'17 (Proc. of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining), 2017. Full Applied Data Science Paper (Oral), 8.8%.
    11. User Modeling on Demographic Attributes in Big Mobile Social Networks. code slides
      Yuxiao Dong, Nitesh V. Chawla, Jie Tang, Yang Yang, Yang Yang.
      TOIS 2017 (ACM Transactions on Information Systems), 2017 (accepted).
    12. UAPD: Inferring Urban Anomalies from Spatial-Temporal Data. code&data slides_by_Xian
      Xian Wu, Yuxiao Dong, Chao Huang, Jian Xu, Nitesh V. Chawla.
      ECML/PKDD'17 (Proc. of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases), 2017. Full Paper, 27%.
    13. Do the Young Live in a "Smaller World" Than the Old? Age-Specific Degrees of Separation in Human Communication.
      Yuxiao Dong§, Omar Lizardo§, Nitesh V. Chawla. (§Equal Contribution)
      PrePrint 2016, arXiv:1606.07556.
    14. Can Scientific Impact Be Predicted? data bibtex
      Yuxiao Dong§, Reid A. Johnson§, Nitesh V. Chawla. (§Equal Contribution)
      TBD 2016 (IEEE Transactions on Big Data), 2016. Full Paper.
    15. Deep Learning for Network Analysis: Problems, Approaches and Challenges.
      Siddharth Pal, Yuxiao Dong, Bishal Thapa, Nitesh V Chawla, Ananthram Swami, Ram Ramanathan.
      MILCOM'16 (Proc. of 2016 IEEE Military Communications Conference), 2016. Full Paper.
    16. Will This Paper Increase Your h-index? Scientific Impact Prediction. slides poster data bibtex
      Yuxiao Dong, Reid A. Johnson, Nitesh V. Chawla.
      WSDM'15 (Proc. of the 8th ACM International Conference on Web Search and Data Mining), 2015. Full Paper, 16.4%.
      Best Paper Award Nomination
    17. Inferring Unusual Crowd Events From Mobile Phone Call Detail Records. slides bibtex
      Yuxiao Dong, Fabio Pinelli, Yiannis Gkoufas, Zubair Nabi, Francesco Calabrese, Nitesh V. Chawla.
      ECML/PKDD'15 (Proc. of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases), 2015. Full Paper, 23%.
    18. Inferring Social Status and Rich Club Effects in Enterprise Communication Networks. plos supporting info slides bibtex
      Yuxiao Dong, Jie Tang, Nitesh V. Chawla, Tiancheng Lou, Yang Yang, Bai Wang.
      PLoS ONE 2015. DOI: 10.1371/journal.pone.0119446. March 2015. (if2013=3.534).
    19. Collaboration Signatures Reveal Scientific Impact slides_by_reid data bibtex
      Yuxiao Dong, Reid A. Johnson, Yang Yang, Nitesh V. Chawla.
      ASONAM'15 (Proc. of the 2015 IEEE/ACM International Conference on Advances in Social Network Analysis and Mining), 2015. Full Paper.
    20. Inferring User Demographics and Social Strategies in Mobile Social Networks. slides poster madness code bibtex ACM TOIS journal version
      Yuxiao Dong, Yang Yang, Jie Tang, Yang Yang, Nitesh V. Chawla.
      KDD'14 (Proc. of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining), 2014. Full Research Paper (Oral), 14.6%.
      Featured on United Nations Global Pulse Notre Dame News ACM TechNews phys.org
    21. Predicting Node Degree Centrality with the Node Prominence Profile. scirep supporting info
      Yang Yang, Yuxiao Dong, Nitesh V. Chawla.
      Scientific Reports 2014. DOI:10.1038/srep07236, November 2014. (if2013=5.078).
      Featured on Notre Dame News
    22. A Novel Genetic Algorithm for Overlapping Community Detection. code bibtex
      Yanan Cai, Chuan Shi, Yuxiao Dong, Qing Ke, Bin Wu.
      ADMA'11 (Proc. of the 7th International Conference on Advanced Data Mining and Applications), 2011.
      Best Application Paper Award

    Invited Talks

    1. 2019: Invited Talk at NetSci'19 Satellite on Quantifying Success.
    2. 2019: Invited Talk at NetSci'19 Satellite on Network Representation Learning.
    3. 2018: Invited Talk at NetSci'18 Higher-Order Models in Network Science Satellite (HONS'18).
    4. 2018: Invited Talk at NICO, Northwestern University, IL.
    5. 2017: Invited Talk at Labs in Tsinghua University.
    6. 2016: Keynote at ACM JCDL'16 Workshop on Mining Scientific Publications (WOSP'16).
    7. 2016: Invited Talks at Labs in Stanford University, Tsinghua University, & Chinese Academy of Sciences.
    8. 2015: Invited Talks at Labs in Oxford University, & Hesburgh Library at University of Notre Dame.

    Professional Activities

    Conference/Workshop Organizers:

    1. ECML/PKDD'20 Applied Data Science Track PC Co-Chair
    2. SIAM SDM'20 Workshop Co-Chair
    3. KDD'19 Deep Learning Day Co-Chair
    4. KDD'18 Deep Learning Day Co-Chair
    5. Co-Chair of DL4G-SDE'19: The International Workshop on Deep Learning for Graphs and Structured Data Embedding at WWW'19.
    6. Co-Chair of BigNet'18: The International Workshop on Learning Representations for Big Networks at WWW'18.
    7. Co-Chair of BigNet'17: The International Workshop on Big Network Analytics at WWW'17.

    Conference PC members:

    1. 2019: KDD, WSDM, WWW, AAAI, SDM
    2. 2018: KDD, WSDM, WWW, ICDM, SDM, ECML/PKDD, DSAA
    3. 2017: KDD, WSDM, WWW, SDM, ASONAM, CIKM
    4. 2016: ASONAM, CIKM
    5. 2015: ASONAM

    Journal Reviewers:

    1. Nature Human Behavior
    2. Nature Scientific Reports
    3. CSUR, ACM Computing Surveys
    4. TKDD, ACM Transactions on the Knowledge Discovery from Data
    5. TWEB, ACM Transactions on the Web
    6. TKDE, IEEE Transactions on Knowledge and Data Engineering
    7. TMC, IEEE Transactions on Mobile Computing
    8. TBD, IEEE Transactions on Big Data
    9. JMLR, Journal of Machine Learning Research