Source: https://ericdongyx.github.io/
Timestamp: 2019-04-23 12:55:11+00:00

Document:
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 profile.
KDD'18 Tutorial on Social & Information Networks: Computational Models for Social and Information Network Analysis.
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.
WWW'18 Workshop on Network Embedding (BigNet'18): The 3rd International Workshop on Learning Representations for Big Networks (BigNet@WWW2018).
WWW'19 (Proc. of the 2019 Web Conference), 2019. Full paper (Oral).
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%.
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.
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%.
RESTFul: Resolution-Aware Forecasting of Behavioral Time Series Data.
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).
Xian Wu, Yuxiao Dong, Baoxu Shi, Ananthram Swami, Nitesh V. Chawla.
SDM'18 (Proc. of the SIAM International Conference on Data Mining), 2018 (accepted).
Will Triadic Closure Strengthen Ties in Social Networks?
Hong Huang, Yuxiao Dong, Jie Tang, Hongxia Yang, Nitesh V. Chawla, Xiaoming Fu.
TKDD 2018 (ACM Transactions on Knowledge Discovery from Data), 2018 (accepted).
Ph.D. dissertation, University of Notre Dame, 2017.
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%.
Yuxiao Dong, Reid A. Johnson, Jian Xu, Nitesh V. Chawla.
KDD'17 (Proc. of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining), 2017. Full Research Paper, 17.5%.
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%.
Yuxiao Dong, Nitesh V. Chawla, Jie Tang, Yang Yang, Yang Yang.
TOIS 2017 (ACM Transactions on Information Systems), 2017 (accepted).
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%.
Do the Young Live in a "Smaller World" Than the Old? Age-Specific Degrees of Separation in Human Communication.
TBD 2016 (IEEE Transactions on Big Data), 2016. Full Paper.
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.
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%.
Yuxiao Dong, Jing Zhang, Jie Tang, Nitesh V. Chawla, Bai Wang.
KDD'15 (Proc. of the 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining), 2015. Full Research Paper (Oral), 19%.
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%.
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).
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.
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%.
Yang Yang, Yuxiao Dong, Nitesh V. Chawla.
Scientific Reports 2014. DOI:10.1038/srep07236, November 2014. (if2013=5.078).
Yuxiao Dong, Jie Tang, Tiancheng Lou, Bin Wu, Nitesh V. Chawla.
ECML/PKDD'13 (Proc. of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases), 2013. Full Paper, 25%.
Chuan Shi, Yanan Cai, Di Fu, Yuxiao Dong, Bin Wu.
DKE 2013 (Data and Knowledge Engineering), 2013.
Yuxiao Dong, Jie Tang, Sen Wu, Jilei Tian, Nitesh V. Chawla, Jinghai Rao, Huanhuan Cao.
ICDM'12 (Proc. of the 12th IEEE International Conference on Data Mining), 2012. Full Paper, 10.7%.
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.
2019: Invited Talk at NetSci'19 Satellite on Network Representation Learning.
2018: Invited Talk at NetSci'18 Higher-Order Models in Network Science Satellite (HONS'18).
2018: Invited Talk at NICO, Northwestern University, IL.
2017: Invited Talk at Labs in Tsinghua University.
2016: Keynote at ACM JCDL'16 Workshop on Mining Scientific Publications (WOSP'16).
2016: Invited Talks at Labs in Stanford University, Tsinghua University, & Chinese Academy of Sciences.
2015: Invited Talks at Labs in Oxford University, & Hesburgh Library at University of Notre Dame.
Co-Chair of BigNet'18: The International Workshop on Learning Representations for Big Networks at WWW'18.
Co-Chair of BigNet'17: The International Workshop on Big Network Analytics at WWW'17.

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