Research

Research Interests

  • Graph Neural Networks, Graph Mining, Structured & Dynamic Data
  • Deep Learning, Deep Generative Models
  • AI for Healthcare, Drug Discovery
  • Social Networks, Network Science, Complex Systems

Research Experiences

  • March 2020 - Present, Boehringer Ingelheim Pharmaceuticals, Inc., Biostatistics & Data Science Americas
  • February 2019 - Present, Weill Cornell Medicine, Cornell University, working with Prof. Fei Wang
  • June 2017 - May 2018, Center for Complex Network Research, working with Prof. Albert-László Barabási
  • Summer 2015 & 2016, working with visiting Prof. Christos Faloutsos from Carnegie Mellon University
  • Summer 2014 & 2015, working with visiting Prof. Chaoming Song from Miami University
  • September 2013 - January 2019 , Department of Computer Science, Tsinghua University. Advisors Prof. Wenwu Zhu and Prof. Peng Cui
  • March 2011 - May 2012, Department of Computer Science, Sun Yat-sen University. Advisor: Prof. Jiwu Huang

Education

Tutorials

T2 Recent Advances on Graph Analytics and Its Applications in Healthcare
Fei Wang (Cornell University); Peng Cui (Tsinghua University); Jian Pei (Simon Fraser University); Yangqiu Song (Hong Kong University of Science and Technology); Chengxi Zang (Cornell University).
KDD 2020 Tutorial on on August 23rd
[Webpage]
[PDF]
T1 Differential Deep Learning on Graphs and its Applications
Chengxi Zang (Cornell University) and Fei Wang (Cornell University).
AAAI 2020 Tutorial on February 7, 2020, New York City, NY.
[Webpage]
[PDF]

Publications

Journal Papers

J2 Exploring the collective human behavior in cascading systems: a comprehensive framework
Yunfei Lu, Linyun Yu, Tianyang Zhang, Chengxi Zang, Peng Cui, Chaoming Song & Wenwu Zhu.
Knowledge and Information Systems (KAIS), 2020.
[PDF]
J1 On Power Law Growth of Social Networks.
Chengxi Zang, Peng Cui, Christos Faloutsos, Wenwu Zhu.
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2018
[PDF]
[Code]

Conference Papers

C12 Neural Dynamics on Complex Networks
Chengxi Zang and Fei Wang.
KDD '20: Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (Accept Rate 216/1279 = 16.89%, Full Paper)
[PDF]
[Slides]
[YouTube]
[Code]
C11 MoFlow: An Invertible Flow Model for Generating Molecular Graphs
Chengxi Zang and Fei Wang.
KDD '20: Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (Accept Rate 216/1279 = 16.89%, Full Paper)
[PDF]
[Slides]
[YouTube]
[Code]
C10 Recent Advances on Graph Analytics and Its Applications in Healthcare
Fei Wang , Peng Cui , Jian Pei , Yangqiu Song , Chengxi Zang
KDD '20: Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining
[PDF]
[Webpage]
C9 Dynamical Origins of Distribution Functions
Chengxi Zang, Peng Cui, Wenwu Zhu, and Fei Wang.
KDD '19: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (Accept Rate (110 oral + 60 poster)/1200 = 14.2%, Oral)
[PDF]
C8 Uncovering Pattern Formation of Information Flow.
Chengxi Zang, Peng Cui, Chaoming Song, Wenwu Zhu, and Fei Wang.
KDD '19: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (Accept Rate (110 oral + 60 poster)/1200 = 14.2%, Poster)
[PDF]
C7 Fates of Microscopic Social Ecosystems: Keep Alive or Dead?
Haoyang Li, Peng Cui, Chengxi Zang, Tianyang Zhang, Wenwu Zhu, and Yishi Lin.
KDD '19: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (Accept Rate (110 oral + 60 poster)/1200 = 14.2%, Oral)
[PDF]
C6 Uncovering the Co-driven Mechanism of Social and Content Links in User Churn Phenomena
Yunfei Lu, Lingyun Yu, Peng Cui, Chengxi Zang, Renzhe Xu, Yihao Liu, Lei Li, and Wenwu Zhu.
KDD '19: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (Accept Rate (45 oral + 100 poster)/700 = 20.7%, Poster, Applied Data Science Track)
[PDF]
C5 Learning and Interpreting Complex Distributions in Empirical Data
Chengxi Zang, Peng Cui, Wenwu Zhu.
KDD '18: Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (Accept Rate 181/983 = 18.4%, Oral)
[PDF]
[PPT]
C4 Collective Human Behavior in Cascading System: Discovery, Modeling and Applications.
Yunfei Lu, Linyun Yu, Tianyang Zhang, Chengxi Zang, Peng Cui, Chaoming Song, and Wenwu Zhu.
2018 IEEE International Conference on Data Mining (ICDM'18). (Acceptance Rate 84/948 =8.86%, Full Paper, Best Paper Candidate)
[PDF]
C3 Long Short Memory Process: Modeling Growth Dynamics of Microscopic Social Connectivity.
Chengxi Zang, Peng Cui, Christos Faloutsos, Wenwu Zhu.
KDD '17: Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (Accept Rate 131/748 = 17.5%, Oral)
[PDF]
[PPT]
[Poster]
[Code]
[Video 1 or 2]
C2 Quantifying Structural Patterns of Information Cascades.
Chengxi Zang, Peng Cui, Chaoming Song, Christos Faloutsos, Wenwu Zhu.
International World Wide Web Conference (WWW), Poster, 2017. (Accept Rate 67/166 = 40.4%)
[PDF]
[PPT]
[Poster]
C1 Beyond Sigmoids: the NetTide Model for Social Network Growth, and its Applications.
Chengxi Zang, Peng Cui, Christos Faloutsos.
KDD '16: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (Accept Rate 142/784 = 18.1%)
[PDF]
[PPT]
[Poster]
[Code]

Workshop Papers & Others

W6 Visualizing Deep Graph Generative Models for Drug Discovery
Karan Yang, Chengxi Zang, Fei Wang
2020 KDD Workshop on Applied Data Science for Healthcare
[PDF]
[Webpage]
W5 MoFlow: An Invertible Flow Model for Molecular Graph Generation
Chengxi Zang, Fei Wang
2020 ICML Workshop on Invertible Neural Networks, Normalizing Flows, and Explicit Likelihood Models (INNF+2020)
[PDF]
[Webpage]
W4 Neural Dynamics on Complex Networks
Chengxi Zang and Fei Wang.
2020 AAAI Deep Learning on Graphs: Methodologies and Applications (DLGMA’20) workshop (Best Paper Award)
[PDF]
[Webpage]
W3 Causation-Driven Visualizations for Insurance Recommendation
Zhixiu Liu, Chengxi Zang, Kun Kuang, Hao Zou, Hu Zheng, and Peng Cui
IEEE International Conference on Multimedia & Expo (ICME), 2019, the Cross-media Analysis for Semantic Knowledge Reasoning and Transfer Workshop.
[PDF]
W2 Modeling the Dynamics of WeChat Social System.
Chengxi Zang, Peng Cui, Linyun Yu, Tianyang Zhang, Wenwu Zhu, Hao Ye.
Draft
[PDF]
W1 Structural Patterns of Information Cascades and their Implications for Dynamics and Semantics.
Chengxi Zang, Peng Cui, Chaoming Song, Christos Faloutsos, Wenwu Zhu.
arXiv Draft
[PDF]

Ph.D. Dissertation

D1 Data-Driven Dynamical Modeling of Complex Social Systems (复杂社交系统的数据驱动动力学建模研究)
Chengxi Zang
Defense Committee Members: Prof. Xindong Wu, Prof. Jianyong Wang, Prof. Jie Tang, Prof. Huawei Shen, Prof. Dan Li, and Prof. Wenwu Zhu
[PDF]
[Webpage]

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