Ph.D. of Computer Science at Arizona State University Research Assistant Professor at Biocomplexity Institute, University of Virginia Email: chenannie45 [at] gmail [dot] com, zrh6du [at] virginia [dot] edu |
I am now a Research Assistant Professor at Biocomplexity Institute, University of Virginia. Before that, I was a software engineer at Google. I received my Ph.D. in Computer Science at Arizona State Univeristy under the supervision of Professor Hanghang Tong in 2019, my M.Sc degree from New York University in 2013 and B.Eng degree from Beihang University in 2011, both majored in Computer Science.
My research interest is in large scale data mining on graphs, machine learning, and computational epidemiology.
Books:
Chen Chen, Hanghang Tong. Network Connectivity: Concepts, Computation, and Optimization. Morgan & Claypool Publishers, 2022. [website]
Journal Papers:
Song Wang, Yushun Dong, Xiao Huang, Chen Chen, Jundong Li. Learning Hierarchical Task Structures for Few-shot Graph Classification. ACM Transactions on Knowledge Discovery from Data (TKDD), 2023. [pdf]
Yushun Dong, Jing Ma, Song Wang, Chen Chen, Jundong Li. Fairness in Graph Mining: A Survey. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023. [pdf]
Zirou Qiu, Baltazar Espinoza, Vitor V Vasconcelos, Chen Chen, Sara M Constantino, Stefani A Crabtree, Luojun Yang, Anil Vullikanti, Jiangzhuo Chen, Jörgen Weibull, Kaushik Basu, Avinash Dixit, Simon A Levin, Madhav V Marathe. Understanding the Coevolution of Mask Wearing and Epidemics: A Network Perspective. Proceedings of the National Academy of Sciences (PNAS), 2022. [pdf]
Chen Chen, Ruiyue Peng, Lei Ying, Hanghang Tong. Fast Connectivity Minimization on Large-scale Networks. ACM Transactions on Knowledge Discovery from Data, 2021. [pdf]
Chen Chen, Yinglong Xia, Hui Zang, Jundong Li, Huan Liu, Hanghang Tong. Incremental One-Class Collaborative Filtering with Co-Evolving Side Networks. Knowledge and Information Systems (KAIS), 2021. [pdf]
Chen Chen, Jingrui He, Nadya Bliss, Hanghang Tong. Towards Optimal Connectivity on Multi-Layered Networks. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2017 [pdf]
Chen Chen, Hanghang Tong, Lei Xie, Lei Ying, Qing He. Cross-Dependency Inference in Multi-layered Networks: A Collaborative Filtering Perspective. ACM Transactions on Knowledge Discovery in Data (TKDD), 2017. (KDD2016 Special Issue) [pdf]
Chen Chen and Hanghang Tong. On the Eigen-Functions of Dynamic Graphs: Fast Tracking and Attribution Algorithms. Statistical Analysis and Data Mining (SAM), 2017. (SDM2015 Special Issue) [pdf]
Chen Chen, Hanghang Tong, B. Aditya Prakash, Tina Eliassi-Rad, Michalis Faloutsos and Christos Faloutsos. Eigen-Optimization on Large Graphs by Edge Manipulation. ACM Transactions on Knowledge Discovery in Data (TKDD), 2016. [pdf]
Chen Chen, Hanghang Tong, B. Aditya Prakash, Charalampos E. Tsourakakis, Tina Eliassi-Rad, Christos Faloutsos, Duen Horng Chau. Node Immunization on Large Graphs: Theory and Algorithms. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2016. [pdf][code]
Conference Papers
Binchi Zhang, Yushun Dong, Chen Chen, Yada Zhu, Minnan Luo, Jundong Li. Adversarial Attacks on Fairness of Graph Neural Networks. ICLR 2024. [pdf]
Jing Ma, Chen Chen, Anil Vullikanti, Ritwick Mishra, Gregory Madden, Daniel Borrajo, Jundong Li. A Look into Causal Effects under Entangled Treatment in Graphs: Investigating the Impact of Contact on MRSA Infection. KDD 2023. [pdf]
Song Wang, Xingbo Fu, Kaize Ding, Chen Chen, Huiyuan Chen, Jundong Li. Federated Few-shot Learning. KDD 2023. [pdf]
Xingbo Fu, Chen Chen, Yushun Dong, Anil Vullikanti, Eili Klein, Gregory Madden, Jundong Li. Spatial-Temporal Networks for Antibiogram Pattern Prediction. ICHI 2023. [pdf]
Zirou Qiu, Andrew Yuan, Chen Chen, Madhav V. Marathe, S. S. Ravi, Daniel J. Rosenkrantz, Richard E. Stearns, Anil Vullikanti. Assigning Agents to Increase Network-Based Neighborhood Diversity. AAMAS 2023. [pdf]
Zirou Qiu, Chen Chen, Madhav Marathe, SS Ravi, Daniel Rosenkrantz, Richard Stearns, Anil Vullikanti. Networked Anti-Coordination Games Meet Graphical Dynamical Systems: Equilibria and Convergence. AAAI 2023. [pdf]
Song Wang, Yushun Dong, Kaize Ding, Chen Chen, Jundong Li. Few-shot Node Classification with Extremely Weak Supervision. WSDM 2023. [pdf]
Song Wang, Chen Chen, Jundong Li. Graph Few-shot Learning with Task-specific Structures. NeurIPS 2022. [pdf]
Song Wang, Kaize Ding, Chuxu Zhang, Chen Chen, Jundong Li. Task-Adaptive Few-shot Node Classification. KDD 2022. [pdf]
Wanjie Tao, Liangyue Li, Chen Chen, Zulong Chen, Hong Wen. When Online Meets Offline: Exploring Periodicity for Travel Destination Prediction. SIGIR 2022. [pdf]
Song Wang, Yushun Dong, Xiao Huang, Chen Chen, Jundong Li. FAITH: Few-Shot Graph Classification with Hierarchical Task Graphs. IJCAI 2022. [pdf]
Zirou Qiu, Chen Chen, Madhav V Marathe, SS Ravi, Daniel J Rosenkrantz, Richard E Stearns, Anil Vullikanti. Finding Nontrivial Minimum Fixed Points in Discrete Dynamical Systems: Complexity, Special Case Algorithms and Heuristics. AAAI 2022. [pdf]
Jack Heavey, Jiaming Cui, Chen Chen, B Aditya Prakash, Anil Vullikanti. Provable Sensor Sets for Epidemic Detection over Networks with Minimum Delay. AAAI 2022. [pdf]
Song Wang, Xiao Huang, Chen Chen, Liang Wu, Jundong Li. REFORM: Error-Aware Few-Shot Knowledge Graph Completion. CIKM 2021. [pdf]
Xiaoying Xing, Hongfu Liu, Chen Chen, Jundong Li. Fairness-Aware Unsupervised Feature Selection. CIKM 2021. [pdf]
Jing Ma, Ruocheng Guo, Chen Chen, Aidong Zhang, Jundong Li. Deconfounding with Networked Observational Data in a Dynamic Environment. WSDM 2021. [pdf]
Yuzhe Zhang, Chen Chen, Minnan Luo, Jundong Li, Caixia Yan, Qinghua Zheng. Unsupervised Hierarchical Feature Selection on Networked Data. DASFAA 2020. [pdf]
Zhen Peng, Minnan Luo, Jundong Li, Chen Chen, Qinghua Zheng. Heterogeneous Information Network Hashing for Fast Nearest Neighbor Search. DASFAA 2019. [pdf]
Chen Chen, Ruiyue Peng, Lei Ying, Hanghang Tong. Network Connectivity Optimization: Fundamental Limits and Effective Algorithms. KDD 2018. [pdf]
Chen Chen. Connectivity in Complex Networks: Measures, Inference and Optimization. WSDM 2018. [pdf]
Chen Chen*, Jundong Li*, Hanghang Tong, Huan Liu. Multi-Layered Network Embedding. SDM 2018. [pdf][errata] (*Equal Contribution)
Chen Chen, Hanghang Tong. Network Connectivity in Complex Networks: Measures, Inference and Optimization. SBP-BRiMS 2017. [pdf]
Qiao Liu, Chen Chen, Annie Gao, Hanghang Tong, Lei Xie. VariFunNet, An Integrated Multiscale Modeling Framework to Study the Effects of Rare Non-coding Variants in Genome-wide Association Studies: Applied to Alzheimer's Disease. BIBM 2017. [pdf]
Chen Chen, Hanghang Tong, Lei Xie, Lei Ying, Qing He. FASCINATE: Fast Cross-Layer Dependency Inference on Multi-layered Networks. KDD 2016. [pdf][video][code][slides] (Bests of KDD 2016)
Chen Chen, Jingrui He, Nadya Bliss, Hanghang Tong. On the Connectivity of Multi-layered Networks: Models, Measures and Optimal Control. ICDM 2015. [pdf][slides]
Chen Chen, Hanghang Tong. Fast Eigen-Functions Tracking on Dynamic Graphs. SDM 2015. [pdf][slides] (Bests of SDM 2015)
Organization Committee: ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2024, Student Travel Award Co-chair
Program Committee: ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2021, 2022, 2023
Program Committee: ACM International Conference on Web Search and Data Mining (WSDM), 2021, 2022, 2023, 2024
Program Committee: SIAM International Conference on Data Mining (SDM), 2021, 2022, 2023, 2024
Program Committee: International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2020, 2021, 2022, 2023, 2024
Program Committee: ACM International Conference on Information and Knowledge Management (CIKM), 2017, 2019, 2021
Program Committee: International Joint Conference on Artificial Intelligence (IJCAI), 2019, 2020, 2021, 2022, 2023
Program Committee: AAAI International Conference on Aritificial Intelligence (AAAI), 2019, 2020, 2021, 2022, 2023, 2024
Program Committee: International Conference on Database Systems for Advanced Applications (DASFAA), 2020
Program Committee: CCF Conference on Natural Language Processing and Chinese Computing (NLPCC), 2017, 2019
Program Committee: International Conference on Social Computing, Behavior-Culture Modeling, and Prediction (SBP), 2019
2021: WSDM Outstanding Reviewer
2019: EECS Rising Star
2018: KDD Student Travel Award
2017: SBP-BRiMS Doctor Consortium Student Travel Award
2016: Bests of KDD 2016
2016: KDD Student Travel Award
2015: ICDM Student Travel Award
2015: Bests of SDM 2015
2015: SDM Student Travel Award