Publications

All my publications are available on my  [Google Scholar | DBLP]. Here are some selected papers:

^* indicates equal contribution, underline indicates interns/students I have advised. And I am the corresponding author.

1. [WWW’24] MULAN: Multi-modal Causal Structure Learning and Root Cause Analysis for Microservice Systems.
   Lecheng Zheng, Zhengzhang Chen, Jingrui He, and Haifeng Chen.
   In Proceedings of the ACM on Web Conference 2024, 2024. Oral Presentation (198/2,008).
   [Slides] [Video]

2. [SIGKDD’24] POND: Multi-Source Time Series Domain Adaptation with Information-Aware Prompt Tuning.
   Junxiang Wang, Guangji Bai, Wei Cheng, Zhengzhang Chen, Liang Zhao, and Haifeng Chen.
   In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024.
   [Video]

3. [SIGKDD’23] Interdependent Causal Networks for Root Cause Localization.
   Dongjie Wang, Zhengzhang Chen^*, Jingchao Ni, Liang Tong, Zheng Wang, Yanjie Fu, and Haifeng Chen.
   In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2023.
   [Slides] [Video]

4. [SIGKDD’23] Incremental Causal Graph Learning for Online Root Cause Analysis.
   Dongjie Wang, Zhengzhang Chen, Yanjie Fu, Yanchi Liu, and Haifeng Chen.
   In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2023.
   [Slides] [Video]

5. [NeurIPS’23] Hierarchical Gaussian Mixture based Task Generative Model for Robust Meta-Learning.
   Yizhou Zhang, Jingchao Ni, Wei Cheng, Zhengzhang Chen, Liang Tong, Haifeng Chen, and Yan Liu.
   In Proceedings of the Thirty-seventh Conference on Neural Information Processing Systems, 2023.

6. [arXiv] Domain specialization as the key to make large language models disruptive: A comprehensive survey.
   Chen Ling, Xujiang Zhao, Jiaying Lu, Chengyuan Deng, Can Zheng, Junxiang Wang, Tanmoy Chowdhury, Yun Li, Hejie Cui, Xuchao Zhang, Tianjiao Zhao, Amit Panalkar, Wei Cheng, Haoyu Wang, Yanchi Liu, Zhengzhang Chen, Haifeng Chen, Chris White, Quanquan Gu, Carl Yang, and Liang Zhao.
   arXiv preprint arXiv:2305.18703, 2023.

7. [ICKG’23] GLAD: Content-aware Dynamic Graphs For Log Anomaly Detection.
   Yufei Li, Yanchi Liu, Haoyu Wang, Zhengzhang Chen, Wei Cheng, Yuncong Chen, Wenchao Yu, Haifeng Chen, and Cong Liu.
   IEEE International Conference on Knowledge Graph, 2023.

8. [SIGKDD’22] Towards Learning Disentangled Representations for Time Series.
   Yuening Li, Zhengzhang Chen, Daochen Zha, Mengnan Du, Jingchao Ni, Denghui Zhang, Haifeng Chen, and Xia Hu.
   In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2022.
   [Slides] [Video]

9. [TNNLS] Automated Anomaly Detection via Curiosity-Guided Search and Self-Imitation Learning.
   Yuening Li, Zhengzhang Chen, Daochen Zha, Kaixiong Zhou, Haifeng Jin, Haifeng Chen, and Xia Hu.
   IEEE Transactions on Neural Networks and Learning Systems, 33(6): 2365-2377, 2022.

10. [BigData’22] Towards Robust Graph Neural Networks via Adversarial Contrastive Learning.
    Shen Wang, Zhengzhang Chen, Jingchao Ni, Haifeng Chen, and Philip S. Yu.
    In Proceedings of the IEEE International Conference on Big Data, 2022.

11. [ICLR’22] Superclass-Conditional Gaussian Mixture Model for Learning Fine-Grained Embeddings.
    Jingchao Ni, Wei Cheng, Zhengzhang Chen, Takayoshi Asakura, Tomoya Soma, Sho Kato, and Haifeng Chen.
    In Proceedings of the International Conference on Learning Representations, 2022. (Spotlight Presentation, 5%).
    [Code]

12. [ECML-PKDD’22] Multi-source Inductive Knowledge Graph Transfer.
    Junheng Hao, Lu-An Tang, Yizhou Sun, Zhengzhang Chen, Haifeng Chen, Junghwan Rhee, Zhichun Li, and Wei Wang.
    In Proceedings of the Joint European Conference on Machine Learning and Knowledge Discovery in Databases, 2022.

13. [CVPR’21] FACESEC: A Fine-grained Robustness Evaluation Framework for Face Recognition Systems.
    Liang Tong, Zhengzhang Chen, Jingchao Ni, Wei Cheng, Dongjin Song, Haifeng Chen, and Yevgeniy Vorobeychik.
    In Proceedings of the Conference on Computer Vision and Pattern Recognition, 2021.
    [Code] [Suppl] [Slides]

14. [KDD’21] Multi-Scale One-Class Recurrent Neural Networks for Discrete Event Sequence Anomaly Detection.
    Zhiwei Wang, Zhengzhang Chen, Jingchao Ni, Hui Liu, Haifeng Chen, and Jiliang Tang.
    In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2021.
    [Code] [Slides]

15. [CIKM’21] Interpreting Convolutional Sequence Model by Learning Local Prototypes with Adaptation Regularization.
    Jingchao Ni, Zhengzhang Chen, Wei Cheng, Bo Zong, Dongjin Song, Yanchi Liu, Xuchao Zhang, and Haifeng Chen.
    In Proceedings of the 30th ACM International Conference on Information and Knowledge Management, 2021.

16. [CIKM’21] Structural Temporal Graph Neural Networks for Anomaly Detection in Dynamic Graphs.
    Lei Cai, Zhengzhang Chen, Chen Luo, Jiaping Gui, Jingchao Ni, Ding Li, and Haifeng Chen.
    In Proceedings of the 30th ACM International Conference on Information and Knowledge Management, 2021.
    [Code] [Slides]

17. [ACMMM’21] Convolutional Transformer based Dual Discriminator Generative Adversarial Networks for Video Anomaly Detection.
    Xinyang Feng, Dongjing Song, Yuncong Chen, Zhengzhang Chen, Jingchao Ni, and Haifeng Chen.
    In Proceedings of the 29th ACM International Conference on Multimedia, 2021.

18. [ICDE’21] AutoOD: Neural Architecture Search for Outlier Detection.
    Yuening Li, Zhengzhang Chen, Daochen Zha, Kaixiong Zhou, Haifeng Jin, Haifeng Chen, and Xia Hu.
    In Proceedings of the 37th IEEE International Conference on Data Engineering, Crete, Greece, 2021.

19. [AAAI’21] Dynamic Gaussian Mixture based Deep Generative Model For Robust Forecasting on Sparse Multivariate Time Series.
    Yinjun Wu, Jingchao Ni, Wei Cheng, Bo Zong, Dongjin Song, Zhengzhang Chen, Yanchi Liu, Xuchao Zhang, Haifeng Chen, and Susan Davidson.
    In Proceedings of the 35th AAAI Conference on Advance of Artificial Intelligence, 2021.
    [Code]

20. [IEEE Intelligent Systems] Anomalous Event Sequence Detection.
    Boxiang Dong, Zhengzhang Chen, Hui (Wendy) Wang, Lu-An Tang, Kai Zhang, Ying Lin, Zhichun Li, and Haifeng Chen.
    IEEE Intelligent Systems, 36(3): 5-13, 2021.

21. [IJCNN’21] Privacy-Preserving Fair Machine Learning Without Collecting Sensitive Demographic Data.
    Hui Hu, Mike Borowczak, and Zhengzhang Chen.
    In Proceedings of the International Joint Conference on Neural Networks, 2021.

22. [WWW’20] A Generic Edge-Empowered Graph Convolutional Network via Node-Edge Mutual Enhancement.
    Pengyang Wang, Jiaping Gui, Zhengzhang Chen, Junghwan Rhee, Haifeng Chen, and Yanjie Fu.
    In Proceedings of the Web Conference 2020, Taiwan, China, 2020.

23. [NDSS’20] You Are What You Do: Hunting Stealthy Malware via Data Provenance Analysis.
    Qi Wang, Wajih Ul Hassan, Ding Li, Kangkook Jee, Xiao Yu, Kexuan Zou, Junghwan Rhee, Zhengzhang Chen, Wei Cheng, Carl A. Gunter, and Haifeng Chen.
    In Proceedings of the Network and Distributed System Security Symposium, San Diego, California, USA, 2020.

24. [AAAI’20] Asymmetrical Hierarchical Networks with Attentive Interactions for Interpretable Review-based Recommendation.
    Xin Dong, Jingchao Ni, Wei Cheng, Zhengzhang Chen, Bo Zong, Dongjin Song, Yanchi Liu, Haifeng Chen, and Gerard de Melo.
    In Proceedings of the 33rd AAAI Conference on Artificial Intelligence, New York, USA, 2020.

25. [ICDE’20] APTrace: A Responsive System for Agile Enterprise-Level Causality Analysis.
    Jiaping Gui, Ding Li, Zhengzhang Chen, Junghwan Rhee, Xusheng Xiao, Mu Zhang, Kangkook Jee, Zhichun Li, and Haifeng Chen.
    In Proceedings of the 36th IEEE International Conference on Data Engineering, Dallas, Texas, USA, 2020.

26. [ICDM’20] T2-Net: A Semi-supervised Deep Model for Turbulence Forecasting.
    Denghui Zhang, Yanchi Liu, Wei Cheng, Bo Zong, Jingchao Ni, Zhengzhang Chen, Haifeng Chen, and Hui Xiong.
    In Proceedings of the IEEE International Conference on Data Mining, 2020.

27. [ACSAC’20] This is Why We Can’t Cache Nice Things: Lightning-Fast Threat Hunting Using Suspicion-Based Hierarchical Storage.
    Wajih Ul Hassan, Ding Li, Kangkook Jee, Xiao Yu, Kexuan Zou, Dawei Wang, Zhengzhang Chen, Zhichun Li, Junghwan Rhee, Jiaping Gui, and Adam Bates.
    In Proceedings of Annual Computer Security Applications Conference, 2020.

28. [SecureComm’20] Anomaly Detection on Web-User Behaviors Through Deep Learning.
    Jiaping Gui, Zhengzhang Chen, Xiao Yu, Cristian Lumezanu, and Haifeng Chen.
    In Proceedings of the 16th EAI International Conference on Security and Privacy in Communication Networks, Washington DC, United States, 2020.

29. [IJCAI’19] Heterogeneous Graph Matching Networks for Unknown Malware Detection.
    Shen Wang^*, Zhengzhang Chen^*, Xiao Yu, Ding Li, Jingchao Ni, Lu-An Tang, Jiaping Gui, Zhichun Li, Haifeng Chen, and Philip S. Yu.
    In Proceedings of the 28th International Joint Conference on Artificial Intelligence, Macao, China, August 2019.

30. [SDM’19] Attentional Heterogeneous Graph Neural Network: Application to Program Reidentification.
    Shen Wang, Zhengzhang Chen, Ding Li, Zhichun Li, Lu-An Tang, Jingchao Ni, Junghwan Rhee, Haifeng Chen, and Philip S. Yu.
    In Proceedings of the 19th SIAM International Conference on Data Mining, Alberta, Canada, May 2019.
    [Slides]

31. [NDSS’19] NoDoze: Combatting Threat Alert Fatigue with Automated Provenance Triage.
    Wajih Ul Hassan, Shengjian Guo, Ding Li, Zhengzhang Chen, Kangkook Jee, Zhichun Li, and Adam Bates.
    In Proceedings of the 26th ISOC Network and Distributed System Security Symposium, San Diego, CA, USA, 2019.

32. [SIGKDD’18] TINET: Learning Invariant Networks via Knowledge Transfer.
    Chen Luo^*, Zhengzhang Chen^*, Lu-An Tang, Anshumali Shrivastava, Zhichun Li, Haifeng Chen, and Jieping Ye.
    In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, London, 2018.
    [Slides]

33. [CIKM’18] Behavior-based Community Detection: Application to Host Assessment In Enterprise Information Networks.
    Cheng Cao^*, Zhengzhang Chen^*, James Caverlee, Lu-An Tang, Chen Luo, and Zhichun Li.
    In Proceedings of the 27th ACM International Conference on Information and Knowledge Management, Turin, Italy, 2018.

34. [CIKM’18] Collaborative Alert Ranking for Anomaly Detection.
    Ying Lin^*, Zhengzhang Chen^*, Cheng Cao, Lu-An Tang, Kai Zhang, Wei Cheng, and Zhichun Li.
    In Proceedings of the 27th ACM International Conference on Information and Knowledge Management, Turin, Italy, 2018.

35. [AAAI’17] Distinguish Polarity in Bag-of-words Model Visualization with Regularized Concentration.
    Yusheng Xie, Zhengzhang Chen, Ankit Agrawal, and Alok Choudhary.
    In Proceedings of the 31st AAAI Conference on Artificial Intelligence, San Francisco, USA, 2017.

36. [CIKM’17] Efficient Discovery of Abnormal Event Sequences in Enterprise Security System.
    Boxiang Dong^*, Zhengzhang Chen^*, Hui (Wendy) Wang, Lu-An Tang, Kai Zhang, Ying Lin, Zhichun Li, and Haifeng Chen.
    In Proceedings of the 26th ACM International Conference on Information and Knowledge Management, Pan Pacific, Singapore, 2017.
    [Slides]

37. [KAIS] Silverback+: Scalable Association Mining Via Fast List Intersection For Columnar Social Data.
    Yusheng Xie, Zhengzhang Chen, Diana Palsetia, Goce Trajcevski, Ankit Agrawal, and Alok Choudhary.
    Knowledge and Information Systems, 50(3): 969-997, 2017.

38. [SIGKDD’16] Ranking Causal Anomalies via Temporal and Dynamical Analysis on Vanishing Correlations.
    Wei Cheng, Kai Zhang, Haifeng Chen, Guofei Jiang, Zhengzhang Chen, and Wei Wang.
    In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Francisco, 2016. (Best Paper Award Runner-Up).
    [Code]

39. [SIGKDD’16] Annealed Sparsity via Adaptive and Dynamic Shrinking.
    Kai Zhang, Shandian Shan, Chaoran Cheng, Zhi Wei, Zhengzhang Chen, Haifeng Chen, Guofei Jiang, Yuan Qi, and Jieping Ye.
    In Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Francisco, 2016.

40. [IJCAI’16] Entity Embedding-based Anomaly Detection for Heterogeneous Categorical Events.
    Ting Chen, Lu-An Tang, Yizhou Sun, Zhengzhang Chen, and Kai Zhang.
    In Proceedings of the 25th International Joint Conference on Artificial Intelligence, New York, July 2016.

41. [SDM’16] Integrating Community and Role Detection in Information Networks.
    Ting Chen, Lu-An Tang, Yizhou Sun, Zhengzhang Chen, Haifeng Chen, and Guofei Jiang.
    In Proceedings of the 16th SIAM International Conference on Data Mining, Miami, FL, May 2016.

42. [Neurocomputing] Enhancing Semi-supervised Learning through Label-aware Base Kernels.
    Qiaojun Wang, Kai Zhang, Zhengzhang Chen, Dequan Wang, Guofei Jiang, and Ivan Marsic.
    Neurocomputing, 2016.

43. [SDM’15] From Categorical to Numerical: Multiple Transitive Distance Learning and Embedding.
    Kai Zhang, Qiaojun Wang, Zhengzhang Chen, Ivan Marsic, Vipin Kumar, and Geoff Jiang.
    In Proceedings of the 15th SIAM International Conference on Data Mining, Vancouver, British Columbia, Canada, 2015.

44. [HPC’15] Incremental, Distributed Single-Linkage Hierarchical Clustering Algorithm Using MapReduce.
    Chen Jin, Zhengzhang Chen, William Hendrix, Md. Mostofa Ali Patwary, Ankit Agrawal, Wei-keng Liao, and Alok Choudhary.
    In Proceedings of the 23rd High Performance Computing Symposium, Alexandria, VA, USA, 2015.

45. [IC3’15] Pruned Search: A Machine Learning based Meta-heuristic Approach for Constrained Continuous Optimization.
    Ruoqian Liu, Ankit Agrawal, Wei-keng Liao, Alok Choudhary, and Zhengzhang Chen.
    In Proceedings of the Eighth International Conference on Contemporary Computing, Noida, India, 2015.

46. [BigDataService’15] A Scalable Hierarchical Clustering Algorithm Using Spark.
    Chen Jin, Ruoqian Liu, Zhengzhang Chen, William Hendrix, Ankit Agrawal, and Alok Choudhary.
    In Proceedings of the IEEE First International Conference on Big Data Computing Service and Applications, Shanghai, China, 2015.

47. [CCGrid ‘15] Running MAP Inference on Million Node Graphical Models: A High Performance Computing Perspective.
    Chen Jin, Qiang Fu, Huahua Wang, William Hendrix, Zhengzhang Chen, Ankit Agrawal, Arindam Banerjee, and Alok Choudhary.
    In Proceedings of the 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, Redwood City, USA, 2015.

48. [Scientific Reports] A Predictive Machine Learning Approach for Microstructure Optimization and Materials Design.
    Ruoqian Liu, Abhishek Kumar, Zhengzhang Chen, Ankit Agrawal, Veera Sundararaghavan, and Alok Choudhary.
    Nature Scientific Reports, vol. 5, no. 11551, 2015.

49. [SC’14] NUMARCK: Machine Learning Algorithm for Resiliency and Checkpointing.
    Zhengzhang Chen, Seung Woo Son, William Hendrix, Ankit Agrawal, Wei-keng Liao, and Alok Choudhary.
    In Proceedings of International Conference for High Performance Computing, Networking, Storage, and Analysis (SC), New Orleans, Louisiana, USA, 2014.

50. [Supercomputing Frontiers] Data Compression for the Exascale Computing Era–Survey.
    Seung Woo Son, Zhengzhang Chen, William Hendrix, Ankit Agrawal, Wei-keng Liao, and Alok Choudhary.
    Supercomputing Frontiers and Innovations, 2014.

51. [ASONAM’14] Indexing Bipartite Memberships in Web Graphs.
    Yusheng Xie, Zhengzhang Chen, Diana Palsetia, Ankit Agrawal, and Alok Choudhary.
    In Proceedings of The IEEE/ACM International Conference on Advances in Social Network Analysis and Mining, Beijing, China, 2014.

52. [SDM’14] Batch Mode Active Learning with Hierarchical-Structured Embedded Variance.
    Yu Cheng, Zhengzhang Chen, Hongliang Fei, Fei Wang, and Alok Choudhary.
    In Proceedings of the 14th SIAM International Conference on Data Mining, Philadelphia, Pennsylvania, USA, 2014.

53. [Theoretical Computer Science] Solving the Maximum Duo-preservation String Mapping Problem with Linear Programming.
    Wenbin Chen, Zhengzhang Chen, Nagiza F. Samatova, Lingxi Peng, Jianxiong Wang, and Maobin Tang.
    Theoretical Computer Science, 2014.

54. [CIKM’13] Feedback-Driven Multiclass Active Learning for Data Streams.
    Yu Cheng, Zhengzhang Chen, Lu Liu, Jiang Wang, Ankit Agrawal, and Alok Choudhary.
    In Proceedings of the 22nd ACM International Conference on Information and Knowledge Management, San Francisco, USA, 2013.

55. [CIKM’13] Bootstrapping Active Name Disambiguation with Crowdsourcing.
    Yu Cheng, Zhengzhang Chen, Kunpeng Zhang, Jiang Wang, Ankit Agrawal, and Alok Choudhary.
    In Proceedings of the 22nd ACM International Conference on Information and Knowledge Management, San Francisco, USA, 2013.

56. [CIKM’13] Random Walk-based Graphical Sampling in Unbalanced Heterogeneous Bipartite Social Graphs.
    Yusheng Xie, Zhengzhang Chen, Ankit Agrawal, and Alok Choudhary.
    In Proceedings of the 22nd ACM International Conference on Information and Knowledge Management, San Francisco, USA, 2013.

57. [BigData’13] Elver: Recommending Facebook Pages in Cold Start Situation Without Content Features.
    Yusheng Xie, Zhengzhang Chen, Ankit Agrawal, and Alok Choudhary.
    In Proceedings of IEEE International Conference on Big Data, Santa Clara, CA, USA, 2013.

58. [IJCAI’13] Forecast Oriented Classification of Spatio-Temporal Extreme Events.
    Zhengzhang Chen, Yusheng Xie, Yu Cheng, Kunpeng Zhang, Ankit Agrawal, Wei-keng Liao, Nagiza F. Samatova, and Alok Choudhary.
    In Proceedings of the 23rd International Joint Conference on Artificial Intelligence, Beijing, China, August 2013.

59. [IJCAI’13] Detecting and Tracking Disease Outbreaks by Mining Social Media Data.
    Yusheng Xie^*, Zhengzhang Chen^*, Kunpeng Zhang, Yu Cheng, Ankit Agrawal, Wei-keng Liao, and Alok Choudhary.
    In Proceedings of the 23rd International Joint Conference on Artificial Intelligence, Beijing, China, August 2013.
    [Code]

60. [SIGKDD’13] JobMiner: A Real-time System for Mining Job-related Patterns from Social Media.
    Yu Cheng, Yusheng Xie, Zhengzhang Chen, Songtao Guo, Ankit Agrawal, and Alok Choudhary.
    In Proceedings of the 19th ACM SIGKDD Conference on Knowledge, Discovery and Data Mining, Chicago, USA, August 11-14, 2013.

61. [ASONAM’13] A Probabilistic Graphical Model for Brand Reputation Assessment in Social Networks.
    Kunpeng Zhang, Doug Downey, Zhengzhang Chen, Yusheng Xie, Yu Cheng, Ankit Agrawal, Wei-keng Liao, and Alok Choudhary.
    In Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, Niagara Falls, Canada, August 25-28, 2013.

62. [SDM’13] Automatic Detection and Correction of Multi-class Classification Errors Using System Whole-part Relationships.
    Zhengzhang Chen, John Jenkins, Jinfeng Rao, Alok Choudhary, Fredrick Semazzi, Anatoli V. Melechko, Vipin Kumar, and Nagiza F. Samatova.
    In Proceedings of the 13th SIAM International Conference on Data Mining, Austin, Texas, USA, May 2-4, 2013.

63. [SDM’13] Graphical Modeling of Macro Behavioral Targeting in Social Networks.
    Yusheng Xie, Zhengzhang Chen, Kunpeng Zhang, Md. Mostofa Ali Patwary, Yu Cheng, Haotian Liu, Ankit Agrawal, and Alok Choudhary.
    In Proceedings of the 13th SIAM International Conference on Data Mining, Austin, Texas, USA, May 2-4, 2013.

64. [IEEE Intelligent Systems] MuSES: A Multilingual Sentiment Elicitation System for Social Media Data.
    Yusheng Xie, Zhengzhang Chen, Kunpeng Zhang, Yu Cheng, Danial K. Honbo, Ankit Agrawal, and Alok Choudhary.
    IEEE Intelligent Systems, vol. 99, 2013.
    [Code]

65. [DMKD] Discovery of Extreme Events-Related Communities In Contrasting Groups of Physical System Networks.
    Zhengzhang Chen, William Hendrix, Hang Guan, Isaac K. Tetteh, Alok Choudhary, Fredrick Semazzi, Nagiza F. Samatova.
    Data Mining and Knowledge Discovery, vol. 27(2): 225-258, 2013.

66. [Book Chapter] Graph-based Anomaly Detection.
    Kanchana Padmanabhan, Zhengzhang Chen, Sriram Lakshminarasimhan, Siddarth S. Ramaswamy, and Bryan T. Richardson.
    Book Chapter of Practical Data Mining with R, CRC Press, 2013.

67. [BMC Systems Biology] SPICE: Discovery of Phenotype-Determining Component Interplays.
    Zhengzhang Chen, Kanchana Padmanabhan, Andrea M Rocha, Yekaterina Shpanskaya, James R Mihelcic, Kathleen Scott, and Nagiza F. Samatova.
    BMC Systems Biology, vol. 6(1): 40, 2012.

68. [IJCAI’11] Classification of Emerging Extreme Event Tracks in Multi-Variate Spatio-Temporal Physical Systems Using Dynamic Network Structures: Application to Hurricane Track Prediction.
    Huseyin Sencan^*, Zhengzhang Chen^*, William Hendrix, Tatdow Pansombut, Frederick Semazzi, Alok Choudhary, Vipin Kumar, Anatoli V. Melechko, and Nagiza F. Samatova.
    In Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence, Barcelona, Spain, July 2011.

69. [JIIS] Community-based Anomaly Detection in Evolutionary Networks.
    Zhengzhang Chen, William Hendrix, and Nagiza F. Samatova.
    Journal of Intelligent Information Systems: Integrating Artificial Intelligence and Database Technologies, vol. 39(1): 59-85, 2011.

70. [BMC Bioinformatics] Efficient alpha, beta-motif Finder for Identification of Phenotype-related Functional Modules.
    Mathew C Schmidt, Andrea M Rocha, Kanchana Padmanabhan, Zhengzhang Chen, Kathleen Scott, James R. Mihelcic, and Nagiza F. Samatova.
    BMC Bioinformatics, vol. 12(1): 440, 2011.

71. [TCS] Inapproximability Results for Equations over Infinite Groups.
    Wenbin Chen, Dengpan Yin, and Zhengzhang Chen.
    Theoretical Computer Science, 411 (26-28): 2513-2519, 2010.

PhD Thesis

Discovery of Informative and Predictive Patterns in Dynamic Networks of Complex Systems.
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