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Publications

·      Minhua Lin, Zhiwei Zhang, Enyan Dai, Zongyu Wu, Yilong Wang, Xiang Zhang, Suhang Wang. "Are You Using Reliable Graph Prompts? Trojan Prompt Attacks on Graph Neural Networks", Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD), 2025.

·      Zhawnen Chen, Tianchun Wang, Yizhou Wang, Michal Kosinski, Xiang Zhang, Yun Fu, Sheng Li. "Through the Theory of Mind's Eye: Reading Minds with Multimodal Video Large Language Models", Proceedings of the International Joint Conference on Neural Networks (IJCNN), 2025.

·      Tianchun Wang, Dongsheng Luo, Wei Cheng, Haifeng Chen, Xiang Zhang. "DyExplainer: Self-explainable Dynamic Graph Neural Network with Sparse Attentions", ACM Transactions on Knowledge Discovery from Data (TKDD), 2025.

·      Tianchun Wang, Yuanzhou Chen, Zichuan Liu, Zhanwen Chen, Haifeng Chen, Xiang Zhang, Wei Cheng. "Humanizing the Machine: Proxy Attacks to Mislead LLM Detectors", Proceedings of the International Conference on Learning Representations (ICLR), 2025.

·      Minhua Lin, Enyan Dai, Junjie Xu, Jinyuan Jia, Xiang Zhang, Suhang Wang. "Stealing Training Graphs from Graph Neural Networks", Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD), 2025.

·      Junjie Xu, Enyan Dai, Dongsheng Luo, Xiang Zhang, Suhang Wang. "Shape-aware Graph Spectral Learning", Proceedings of the ACM International Conference on Information and Knowledge Management (CIKM), 2024.

·      Tianxiang Zhao, Xiang Zhang, Suhang Wang. " Imbalanced Node Classification with Synthetic Over-sampling", IEEE Transactions on Knowledge and Data Engineering (TKDE), 2024.

·      Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang. "Multi-source Unsupervised Domain Adaptation on Graphs with Transferability Modeling", Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD), 2024.

·      Zongyu Wu, Hongcheng Gao, Yueze Wang, Xiang Zhang, Suhang Wang. "Universal Prompt Optimizer for Safe Text-to-Image Generation", Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2024.

·      Tianxiang Zhao, Xiang Zhang, Suhang Wang. "Disambiguated Node Classification with Graph Neural Networks", Proceedings of the International Conference on World Wide Web (WWW), 2024.

·      Tianchun Wang, Dongsheng Luo, Wei Cheng, Haifeng Chen, Xiang Zhang. "DyExplainer: Explainable Dynamic Graph Neural Networks", Proceedings of the International Conference on Web Search and Data Mining (WSDM), 2024.

·      Tianxiang Zhao, Wenchao Yu, Suhang Wang, Lu Wang, Xiang Zhang, Yuncong Chen, Yanchi Liu, Wei Cheng, Haifeng Chen. "Interpretable Imitation Learning with Dynamic Causal Relations", Proceedings of the International Conference on Web Search and Data Mining (WSDM), 2024.

·       Dongsheng Luo, Tianxiang Zhao, Wei Cheng, Dongkuan Xu, Feng Han, Wenchao Yu, Xiao Liu, Haifeng Chen, Xiang Zhang. "Towards Inductive and Efficient Explanations for General Graph Neural Networks", IEEE Transactions on Pattern Analysis and Machine Intelligence (IEEE TPAMI), 2024.

·       Minhua Lin, Teng Xiao, Enyan Dai, Xiang Zhang, Suhang Wang. "Certifiably Robust Graph Contrastive Learning", Proceedings of the Conference on Neural Information Processing Systems (NeurIPS), 2023.

·       Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang. "Faithful and Consistent Graph Neural Network Explanations with Rationale Alignment", Transactions on Intelligent Systems and Technology (ACM TIST), 2023.

·       Tianxiang Zhao, Wenchao Yu, Suhang Wang, Lu Wang, Xiang Zhang, Yuncong Chen, Yanchi Liu, Wei Cheng, Haifeng Chen. "Skill Disentanglement for Imitation Learning from Suboptimal Demonstrations", Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD), 2023.

·       Tianchun Wang, Farzaneh Mirzazadeh, Xiang Zhang, Jie Chen. "GC-Flow: A Graph-Based Flow Network for Effective Clustering", Proceedings of the International Conference on Machine Learning (ICML), 2023.

·       Enyan Dai, Minhua Lin, Xiang Zhang, Suhang Wang. "Unnoticeable Backdoor Attacks on Graph Neural Networks", Proceedings of the International Conference on World Wide Web (WWW), 2023.

·       Dongsheng Luo, Wei Cheng, Y. Wang, D. Xu, J. Ni, W. Yu, X. Zhang, Y. Liu, Y. Chen, Haifeng Chen, Xiang Zhang. "Time Series Contrastive Learning with Information-Aware Augmentations", Proceedings of the AAAI International Conference on Artificial Intelligence (AAAI), 2023.

·       Dongsheng Luo, Yuchen Bian, Yaowei Yan, Xiong Yu, Jun Huan, Xiao Liu, Xiang Zhang. "Random Walk on Multiple Networks", IEEE Transactions on Knowledge and Data Engineering (TKDE), 2023.

·      Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang. "Towards Faithful and Consistent Explanations for Graph Neural Networks", Proceedings of the International Conference on Web Search and Data Mining (WSDM), 2023.

·       Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang. "TopoImb: Toward Topology-level Imbalance in Learning from Graphs", Learning on Graphs Conference (LoG), 2023.

·       Dongkuan Xu, Subho Mukherjee, Xiaodong Liu, Debadeepta Dey, Wenhui Wang, Xiang Zhang, Ahmed Awadallah, Jianfeng Gao. "AutoMiniLM: Task-agnostic Neural Architecture Search for Distilling Large Language Models", Proceedings of the Conference on Neural Information Processing Systems (NeurIPS), 2022.

·       Tianchun Wang, Wei Cheng, Dongsheng Luo, Wenchao Yu, Jingchao Ni, Liang Tong, Haifeng Chen, and Xiang Zhang, "Personalized Federated Learning via Heterogeneous Modular Networks", Proceedings of the IEEE International Conference on Data Mining (ICDM), 2022.

·       Junjie Xu, Enyan Dai, Xiang Zhang, Suhang Wang. “HP-GMN:Graph Memory Networks for Heterophilous Graphs”, Proceedings of the IEEE International Conference on Data Mining (ICDM), 2022.

·       Tianxiang Zhao, Xiang Zhang, and Suhang Wang. "Self-Supervised Graph Attention for Automatic Edge Disentanglement", Proceedings of the International Conference on World Wide Web (WWW), 2022.

·       Yihang Yin, Qingzhong Wang, Siyu Huang, Haoyi Xiong, Xiang Zhang. "AutoGCL: Automated Graph Contrastive Learning via Learnable View Generators", Proceedings of the AAAI International Conference on Artificial Intelligence (AAAI), 2022.

·       Yihang Yin, Siyu Huang, Xiang Zhang. "BM-NAS: Bilevel Multimodal Neural Architecture Search", Proceedings of the AAAI International Conference on Artificial Intelligence (AAAI), 2022.

·       Dongkuan Xu, Wei Cheng, Dongsheng Luo, Haifeng Chen, and Xiang Zhang. "InfoGCL: Information-Aware Graph Contrastive Learning", Proceedings of the Conference on Neural Information Processing Systems (NeurIPS), 2021. [pdf]

·       Dongsheng Luo, Shuai Ma, Yaowei Yan, Chunming Hu, Xiang Zhang, and Jinpeng Huai. "A Collective Approach to Scholar Name Disambiguation", IEEE Transactions on Knowledge and Data Engineering (TKDE), 2021. [pdf]

·      Yameng Gu, Lucas E. Sainburg, Sizhe Kuang, Feng Han, Jack W. Williams, Yikang Liu, Nanyin Zhang, Xiang Zhang, David A. Leopold, Xiao Liu. "Brain activity fluctuations propagate as waves traversing the cortical hierarchy", Cerebral Cortex, 2021.

·      Dongkuan Xu, Wei Cheng, Jingchao Ni, Dongsheng Luo, Masanao Natsumeda, Dongjin Song, Bo Zong, Xiaojie Zhao, Haifeng Chen, Xiang Zhang. "Deep Multi-Instance Contrastive Learning with Dual Attention for Anomaly Precursor Detection", Proceedings of the SIAM International Conference on Data Mining (SDM), 2021.

·      Dongkuan Xu, Wei Cheng, Xin Dong, Bo Zong, Wenchao Yu, Jingchao Ni, Dongjin Song, Xuchao Zhang, Haifeng Chen, Xiang Zhang. "Multi-Task Recurrent Modular Networks", Proceedings of the AAAI International Conference on Artificial Intelligence (AAAI), 2021.

·      Dongkuan Xu, Junjie Liang, Wei Cheng, Wei Hua, Haifeng Chen, Xiang Zhang. "Transformer-Style Relational Reasoning with Dynamic Memory Updating for Temporal Network Modeling", Proceedings of the AAAI International Conference on Artificial Intelligence (AAAI), 2021.

·      Dongsheng Luo, Yuchen Bian, Jun Huan, Xiang Zhang. "Attentive Social Recommendation: Towards User and Item Diversities", AAAI International Conference on Artificial Intelligence - Workshop on Deep Learning on Graphs: Methods and Applications (AAAI-DLG), 2021.

·      Tianxiang Zhao, Xiang Zhang and Suhang Wang. "GraphSMOTE: Imbalanced Node Classification on Graphs with Graph Neural Networks", Proceedings of the International Conference on Web Search and Data Mining (WSDM), 2021. [pdf]

·      Dongsheng Luo, Wei Cheng, Wenchao Yu, Bo Zong, Jingchao Ni, Haifeng Chen and Xiang Zhang. "Learning to Drop: Robust Graph Neural Network via Topological Denoising", Proceedings of the International Conference on Web Search and Data Mining (WSDM), 2021. [pdf]

·       Dongsheng Luo, Wei Cheng, Dongkuan Xu, Wenchao Yu, Bo Zong, Haifeng Chen, and Xiang Zhang. "Parameterized Explainer for Graph Neural Network", Proceedings of the Conference on Neural Information Processing Systems (NeurIPS), 2020. [pdf]

·       Yuchen Bian, Jun Huan, Dejing Dou, and Xiang Zhang. "Rethinking Local Community Detection: Query Nodes Replacement", Proceedings of the IEEE International Conference on Data Mining (ICDM), 2020. [pdf]

·       Tianxiang Zhao, Xianfeng Tang, Xiang Zhang, Suhang Wang. "Semi-Supervised Graph-to-Graph Translation", Proceedings of the ACM International Conference on Information and Knowledge Management (CIKM), 2020. [pdf]

·       Dongsheng Luo, Yuchen Bian, Yaowei Yan, Xiao Liu, Jun Huan and Xiang Zhang. "Local Community Detection in Multiple Networks", Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD), 2020. [pdf]

·       Feng Han, Yameng Gu, Gregory L Brown, Xiang Zhang, and Xiao Liu. "Neuroimaging contrast across the cortical hierarchy is the feature maximally linked to behavior and demographics", NeuroImage, 2020. [pdf]

·       Heming Wang, Tamar Sofer, Xiang Zhang, Robert Elston, Susan Redline, and Xiaofeng Zhu. "Local Ancestry Inference in Large Pedigrees", Nature Scientific Reports, 2020. [pdf]

·      Dongkuan Xu, Wei Cheng, Bo Zong, Dongjin Song, Jingchao Ni, Wenchao Yu, Yanchi Liu, Haifeng Chen, Xiang Zhang. "Tensorized LSTM with Adaptive Shared Memory for Learning Trends in Multivariate Time Series", Proceedings of the AAAI International Conference on Artificial Intelligence (AAAI), 2020. [pdf]

·      Dongsheng Luo, Jingchao Ni, Suhang Wang, Yuchen Bian, Xiong Yu, and Xiang Zhang. "Deep Multi-Graph Clustering via Attentive Cross-Graph Association", Proceedings of the International Conference on Web Search and Data Mining (WSDM), 2020. [pdf]

·       Wei Cheng, Xiang Zhang, and Wei Wang. "Sparse Regression Models for Unraveling Group and Individual Associations in eQTL Mapping", Methods in Molecular Biology, Springer (New York), 2020. [pdf]

·      Jiang Bian, Weibo Wang, Xiang Zhang, Wei Wang, Arthur Huang, and Zhishan Guo. "On Generating Dominators of Customer Preferences", Proceedings of the IEEE International Conference on Big Data (Big Data), 2019. [pdf]

·       Dongkuan Xu, Wei Cheng, Dongsheng Luo, Yameng Gu, Xiao Liu, Jingchao Ni, Bo Zong, Haifeng Chen, and Xiang Zhang. "Adaptive Neural Network for Node Classification in Dynamic Networks", Proceedings of the IEEE International Conference on Data Mining (ICDM), 2019. [pdf]

·       Yuchen Bian, Dongsheng Luo, Yaowei Yan, Wei Cheng, and Xiang Zhang. "Memory-Based Random Walk for Multi-Query Local Community Detection", Knowledge and Information Systems (KAIS), 2019. [pdf]

·       Dongkuan Xu, Wei Cheng, Dongsheng Luo, Xiao Liu, Xiang Zhang. "Spatio-Temporal Attentive RNN for Node Classification in Temporal Attributed Graphs", Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 2019. [pdf]

·       Yaowei Yan, Yuchen Bian, Dongsheng Luo, Dongwon Lee and Xiang Zhang. "Constrained Local Graph Clustering by Colored Random Walk", Proceedings of the International Conference on World Wide Web (WWW), 2019. [pdf]

·       Dongkuan Xu, Wei Cheng, Bo Zong, Jingchao Ni, Dongjin Song, Wenchao Yu, Haifeng Chen, and Xiang Zhang. "Deep Co-Clustering", Proceedings of the SIAM International Conference on Data Mining (SDM), 2019. [pdf]

·       Yuchen Bian, Yaowei Yan, Wei Cheng, Wei Wang, Dongsheng Luo, and Xiang Zhang. "On Multi-Query Local Community Detection", Proceedings of the IEEE International Conference on Data Mining (ICDM), 2018. [pdf] (Best Paper Candidate) 

·       Yuan Yao, Hanghang Tong, Guo Yan, Feng Xu, Xiang Zhang, Boleslaw Szymanski, Jian Lu. "Dual-Regularized One-Class Collaborative Filtering with Implicit Feedback", World Wide Web Journal (WWWJ), 2018. [pdf]

·       Yuchen Bian, Jingchao Ni, Wei Cheng, and Xiang Zhang. "The Multi-Walker Chain and Its Application in Local Community Detection", Knowledge and Information Systems (KAIS), 2018. [pdf]

·       Yaowei Yan, Dongsheng Luo, Jingchao Ni, Hongliang Fei, Wei Fan, Xiong Yu, John Yen, and Xiang Zhang. "Local Graph Clustering by Multi-Network Random Walk with Restart", Proceedings of the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2018. [pdf]

·       Jingchao Ni, Shiyu Chang, Xiao Liu, Wei Cheng, Haifeng Chen, Dongkuan Xu and Xiang Zhang. "Co-Regularized Deep Multi-Network Embedding", Proceedings of the International Conference on World Wide Web (WWW), 2018. [pdf]

·       Yubao Wu, Xiang Zhang, Yuchen Bian, Zhipeng Cai, Xiang Lian, Fengpan Zhao, Xueting Liao, Syed Hussain. "Second-Order Random Walk Based Proximity Measures in Graph Analysis: Formulations and Algorithms", The VLDB Journal (VLDBJ), 2017. [pdf]

·       Jingchao Ni, Wei Cheng, Wei Fan, and Xiang Zhang. "ComClus: A Self-Grouping Framework for Multi-Network Clustering", IEEE Transactions on Knowledge and Data Engineering (TKDE), 2017. [pdf]

·       Xiaoyin Li, Susan Redline, Xiang Zhang, Scott Williams, and Xiaofeng Zhu. "Height Associated Variants Demonstrate Assortative Mating in Human Populations", Nature Scientific Reports, 2017. [pdf]

·       Yuchen Bian, Jingchao Ni, Wei Cheng, and Xiang Zhang. "Many Heads are Better than One: Local Community Detection by the Multi-Walker Chain", Proceedings of the IEEE International Conference on Data Mining (ICDM), 2017. [pdf] (Best Paper Candidate) 

·      Jingchao Ni, Wei Cheng, Kai Zhang, Dongjin Song, Tan Yan, Haifeng Chen, and Xiang Zhang. "Ranking Causal Anomalies by Modeling Local Propagations on Networked Systems", Proceedings of the IEEE International Conference on Data Mining (ICDM), 2017. [pdf]

·       Jingchao Ni, Hongliang Fei, Wei Fan, and Xiang Zhang. "Automated Medical Diagnosis by Ranking Clusters Across the Symptom-Disease Network", Proceedings of the IEEE International Conference on Data Mining (ICDM), 2017. [pdf]

·       Xiaojin Li, Licong Cui, Shiqiang Tao, Jing Chen, Xiang Zhang, and Guoqiang Zhang. "HyCLASSS: A Hybrid Classifier for Automatic Sleep Stage Scoring", IEEE Journal of Biomedical and Health Informatics (JBHI), 2017. [pdf]

·       Jingchao Ni, Hongliang Fei, Wei Fan, and Xiang Zhang. "Cross-Network Clustering and Cluster Ranking for Medical Diagnosis", Proceedings of the IEEE International Conference on Data Engineering (ICDE), 2017. [pdf]

·       Wei Cheng, Jingchao Ni, Kai Zhang, Haifeng Chen, Guofei Jiang, Yu shi, Xiang Zhang, and Wei Wang. "Ranking Causal Anomalies for System Fault Diagnosis via Temporal and Dynamical Analysis on Vanishing Correlations", ACM Transactions on Knowledge Discovery from Data (TKDD), 2017. [pdf]

·       Yubao Wu, Yuchen Bian, and Xiang Zhang. "Remember Where You Came from: On the Second-Order Random Walk Based Proximity Measures", Proceedings of the VLDB Endowment (PVLDB), 10 (1), 13-24, 2016. [pdf]

·       Heming Wang, Yoonha Choi, Bamidele Tayo, Xuefeng Wang, Xiang Zhang, Uli Broeckel, Craig Hanis, Sharon Kardia, Susan Redline, Richard S Cooper, Hua Tang, and Xiaofeng Zhu. "Genome-Wide Survey in African Americans Demonstrates Potential Epistasis of Fitness in the Human Genome", Genetic Epidemiology, 2016. [pdf]

·       Jingchao Ni, Mehmet Koyuturk, Hanghang Tong, Jonathan Haines, Rong Xu, and Xiang Zhang. "Disease Gene Prioritization by Integrating Tissue-Specific Molecular Networks Using a Robust Multi-Network Model", BMC Bioinformatics, 17 (1), 453, 2016. [pdf] [code]

·       Jingchao Ni, Wei Cheng, Wei Fan, and Xiang Zhang. "Self-Grouping Multi-Network Clustering", Proceedings of the IEEE International Conference on Data Mining (ICDM), 2016. [pdf]

·       Wei Cheng, Xiang Zhang, and Wei Wang. "Robust Methods for Expression Quantitative Trait Loci Mapping", Big Data Analytics in Genomics. Springer (New York), 2016. [pdf]

·       Wei Cheng, Yu Shi, Xiang Zhang, and Wei Wang. "Sparse Regression Models for Unraveling Group and Individual Associations in eQTL Mapping", BMC Bioinformatics, 17 (1), 136, 2016. [pdf]

·       Wei Cheng, Zhishan Guo, Xiang Zhang, and Wei Wang. "CGC: A Flexible and Robust Approach to Integrating Co-Regularized Multi-Domain Graph for Clustering", ACM Transactions on Knowledge Discovery from Data (TKDD), 10 (4), 46, 2016. [pdf]

·       Yubao Wu, Ruoming Jin, and Xiang Zhang. “Efficient and Exact Local Search for Random Walk Based Top-K Proximity Query in Large Graphs”, IEEE Transactions on Knowledge and Data Engineering (TKDE), 28 (5), 1160-1174, 2016. [pdf]

·       Yubao Wu, Xiaofeng Zhu, Li Li, Wei Fan, Ruoming Jin, and Xiang Zhang. “Mining Dual Networks: Models, Algorithms and Applications”, ACM Transactions on Knowledge Discovery from Data (TKDD), 10 (4), 40, 2016. [pdf]

·       Rui Liu, Wei Cheng, Hanghang Tong, Wei Wang, and Xiang Zhang. “Robust Multi-Network Clustering via Joint Cross-Domain Cluster Alignment”, Proceedings of the IEEE International Conference on Data Mining (ICDM), 291-300, 2015. [pdf] (Best Paper Candidate)  

·       Jingchao Ni, Hanghang Tong, Wei Fan, and Xiang Zhang. "Flexible and Robust Multi-Network Clustering", Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD), 835-844, 2015. [pdf][code]

·       Wei Cheng, Xiang Zhang, Feng Pan, and Wei Wang. "HICC: An Entropy Splitting Based Framework for Hierarchical Co-Clustering", Knowledge and Information Systems (KAIS), 46 (2), 343-367, 2015. [pdf]

·       Yubao Wu, Ruoming Jin, Jing Li, and Xiang Zhang. "Robust Local Community Detection: On Free Rider Effect and Its Elimination", Proceedings of the VLDB Endowment (PVLDB), 8 (7): 798-809, 2015. [pdf] [code]

·       Wei Cheng, Yu Shi, Xiang Zhang, and Wei Wang. "Fast and Robust Group-Wise eQTL Mapping Using Sparse Graphical Models", BMC Bioinformatics, 16 (1), 1, 2015. [pdf]

·       Yubao Wu, Ruoming Jin, Xiaofeng Zhu, and Xiang Zhang. "Finding Dense and Connected Subgraphs in Dual Networks", Proceedings of the IEEE International Conference on Data Engineering (ICDE), 915-926, 2015. [pdf] [code]

·       Yang Chen, Xiang Zhang, Guoqiang Zhang, and Rong Xu. "Comparative Analysis of a novel Disease Phenotype Network based on Clinical Manifestations", Journal of Biomedical Informatics, 53, 113-120, 2015. [pdf]

·       Wenhui Wang, Sen Yang, Xiang Zhang, and Jing Li. "Drug Repositioning by Integrating Target Information through a Heterogeneous Network Model", Bioinformatics, 30 (20), 2923-2930, 2014. [pdf]

·       Yuan Yao, Hanghang Tong, Guo Yan, Feng Xu, Xiang Zhang, Boleslaw Szymanski, and Jian Lu. "Dual-Regularized One-Class Collaborative Filtering", Proceedings of the ACM International Conference on Information and Knowledge Management (CIKM), 759-768, 2014. [pdf]

·       Jingchao Ni, Hanghang Tong, Wei Fan, and Xiang Zhang. "Inside the Atoms: Ranking on a Network of Networks", Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD), 1356-1365, 2014. [pdf][code]

·       Yubao Wu, Ruoming Jin, and Xiang Zhang. "Fast and Unified Local Search for Random Walk Based K-Nearest-Neighbor Query in Large Graphs", Proceedings of the ACM International Conference on Management of Data (SIGMOD), 1139-1150, 2014. [pdf][code]

·       Wei Cheng, Xiang Zhang, Zhishan Guo, Yu Shi, and Wei Wang. "Graph Regularized Dual Lasso for Robust eQTL Mapping", Bioinformatics, 30 (12), i139-i148, Special Issue of the Proceedings of the International Conference on Intelligent Systems for Molecular Biology (ISMB), 2014. [pdf]

·       Wei Cheng, Xiaoming Jin, Jiantao Sun, Xuemin Lin, Xiang Zhang, and Wei Wang. “Searching Dimension Incomplete Databases”, IEEE Transactions on Knowledge and Data Engineering (TKDE), 26 (3), 725-738, 2014. [pdf]

·       Yuhai Zhao, Guoren Wang, Xiang Zhang, Jeffrey Yu, and Zhanghui Wang. “Learning Phenotype Structure Using Sequence Model”, IEEE Transactions on Knowledge and Data Engineering (TKDE), 26 (3), 667-681, 2014. [pdf]

·       Hongfei Wang and Xiang Zhang. “Binary Time-Series Query Framework for Efficient Quantitative Trait Association Study”, Proceedings of the IEEE International Conference on Data Mining (ICDM), 777-786, 2013. [pdf]

·       Yubao Wu, Xiaofeng Zhu, Jian Chen, and Xiang Zhang. “EINVis: A Visualization Tool for Exploring Epistatic Interactions Networks in Genetic Association Studies”, Genetic Epidemiology, 37 (7), 675-685, 2013. [pdf]

·       Wei Cheng, Xiang Zhang, Zhishan Guo, Yubao Wu, Patrick Sullivan and Wei Wang. “Flexible and Robust Co-Regularized Multi-Domain Graph Clustering”, Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD), 320-328, 2013. [pdf]

·       Zhaojun Zhang, Shunping Huang, Jack Wang, Xiang Zhang, Fernando Pardo Manuel de Villena, Leonard McMillan, and Wei Wang. “GeneScissors: A Comprehensive Approach to Detecting and Correcting Spurious Transcriptome Inference due to RNAseq Reads Misalignment”, Bioinformatics, 29 (13): i291-299, Special Issue of the Proceedings of the International Conference on Intelligent Systems for Molecular Biology (ISMB), 2013. [pdf]

·       Xiang Zhang, Shunping Huang, Zhaojun Zhang, and Wei Wang. “Mining Genome-Wide Genetic Markers”, PLoS Computational Biology, 8 (12), e1002828, 2012. [pdf]

·       Yi Liu, Zhishan Guo, Xiang Zhang, Vladimir Jojic, and Wei Wang. “Metric Learning from Relative Comparisons by Minimizing Squared Residual”, Proceedings of the IEEE International Conference on Data Mining (ICDM), 978-983, 2012. [pdf]

·       Wei Cheng, Xiang Zhang, Feng Pan, and Wei Wang. “Hierarchical Co-Clustering Based on Entropy Splitting”, Proceedings of the ACM Conference on Information and Knowledge Management (CIKM), 1472-1476, 2012. [pdf]

·       Wei Cheng, Xiang Zhang, Yubao Wu, Xiaolin Yin, Jing Li, David Heckerman, and Wei Wang. “Inferring Novel Associations between SNP Sets and Gene Sets in eQTL Study Using Sparse Graphical Model”, Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine (BCB), 466-472, 2012. [pdf]

·       Xiang Zhang, Shunping Huang, Wei Sun, and Wei Wang. “Rapid and Robust Resampling-based Multiple Testing Correction with Application in Genome-Wide eQTL Study”, Genetics, 190 (4), 1511-1520, 2012. [pdf]

·       Mingsheng Long, Jianmin Wang, Guiguang Ding, Wei Cheng, Xiang Zhang, and Wei Wang. “Dual Transfer Learning”, Proceedings of the SIAM International Conference on Data Mining (SDM), 540-551, 2012. [pdf] (Best Paper Candidate)  

·       Xiang Zhang, Wei Cheng, Jennifer Listgarten, Carl Kadie, Shunping Huang, Wei Wang, and David Heckerman. “Learning Transcriptional Regulatory Relationships Using Sparse Graphical Models”, PLoS One, 7 (5): e35762, 2012. [pdf]

·       Zhaojun Zhang, Xiang Zhang, and Wei Wang. “HTreeQA: Using Semi-Perfect Phylogeny Trees in Quantitative Trait Loci Study on Genotype Data”, G3: Genes, Genomes, Genetics, 2 (2), 175-189, 2012. [pdf]

·       Wei Cheng, Xiaochuan Ni, Jian-Tao Sun, Xiaoming Jin, Hye-Chung Kum, Xiang Zhang, and Wei Wang. “Measuring Opinion Relevance in Latent Topic Space”, Proceedings of the IEEE International Conference on Social Computing (SocialCom), 323-330, 2011. [pdf]

·       Xiang Zhang. “Efficient Algorithms for Detecting Genetic Interactions in Genome-Wide Association Study”, Ph.D. Thesis, University of North Carolina at Chapel Hill, 2011. [pdf] (2012 SIGKDD Dissertation Award Honorable Mention)  

·       Xiang Zhang, Shunping Huang, Fei Zou, and Wei Wang. “Tools for Efficient Epistasis Detection in Genome-Wide Association Study”, Source Code for Biology and Medicine, 6 (1), 1-3, 2011. [pdf]

·       Xiang Zhang, Shunping Huang, Fei Zou, and Wei Wang. “TEAM: Efficient Two-Locus Epistasis Tests in Human Genome-Wide Association Study”, Bioinformatics, 26(12): i217-227, Special Issue of the Proceedings of the International Conference on Intelligent Systems for Molecular Biology (ISMB), 2010. [pdf] [code]

·       Xiang Zhang, Feng Pan, and Wei Wang. “Finding High-Order Correlations in High-Dimensional Biological Data”, Link Mining: Models, Algorithms and Applications (Eds. Yu, Han, and Faloutsos), Chapter 19, 505-534, Springer, 2010. [pdf]

·       Xiang Zhang, Feng Pan, Yuying Xie, Fei Zou, and Wei Wang. “COE: A General Approach for Efficient Genome-Wide Two-Locus Epistasis Test in Disease Association Study”, Journal of Computational Biology (JCB), 17 (3), 401-415, 2010. (Invited submission from RECOMB’09) [pdf]

·       Xiang Zhang, Feng Pan, and Wei Wang. “Efficient Algorithms for Genome-Wide Association Study”, ACM Transactions on Knowledge Discovery from Data (TKDD), 3 (4), 19, 2009. [pdf]

·       Xiang Zhang, Feng Pan, Yuying Xie, Fei Zou, and Wei Wang. “COE: A General Approach for Efficient Genome-Wide Two-Locus Epistasis Test in Disease Association Study”, Proceedings of the International Conference on Research in Computational Molecular Biology (RECOMB), 253-269, 2009. [pdf] [code]

·       Xiang Zhang, Fei Zou, and Wei Wang. “FastChi: an Efficient Algorithm for Analyzing Gene-Gene Interactions”, Proceedings of the Pacific Symposium on Biocomputing (PSB), 528-539, 2009. [pdf]

·       Xiang Zhang, Feng Pan, and Wei Wang. “REDUS: Finding Reducible Subspaces in High Dimensional Data”, Proceedings of the ACM Conference on Information and Knowledge Management (CIKM), 961-970, 2008. [pdf]

·       Xiang Zhang, Feng Pan, Wei Wang, and Andrew Nobel. “Mining Non-Redundant High Order Correlations in Binary Data”, Proceedings of the VLDB Endowment (PVLDB), (1) 1, 1178-1188, 2008. [pdf]

·       Xiang Zhang, Fei Zou, and Wei Wang. “FastANOVA: an Efficient Algorithm for Genome-Wide Association Study”, Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (SIGKDD), 821-829, 2008. [pdf][code] (Best Research Paper Award)  

·       Feng Pan, Xiang Zhang, and Wei Wang. “CRD: Fast Co-clustering on Large Datasets Utilizing Sample-Based Matrix Decomposition”, Proceedings of the ACM International Conference on Management of Data (SIGMOD), 173-184, 2008. [pdf]

·       Xiang Zhang, Feng Pan, and Wei Wang. “CARE: Finding Local Linear Correlations in High Dimensional Data”, Proceedings of the IEEE International Conference on Data Engineering (ICDE), 130-139, 2008. [pdf] (Best Student Paper Award)

·       Feng Pan, Xiang Zhang, and Wei Wang. “A General Framework for Fast Co-Clustering on Large Datasets Using Matrix Decomposition”, Proceedings of the IEEE International Conference on Data Engineering (ICDE), 1337-1339, 2008. [pdf]

·       Xiang Zhang and Wei Wang. “An Efficient Algorithm for Mining Coherent Patterns from Heterogeneous Microarrays”, Proceedings of the International Conference on Scientific and Statistical Database Management (SSDBM), 32, 2007. [pdf]

·       Xiang Zhang, Wei Wang, and Jun Huan. “On Demand Phenotype Ranking through Subspace Clustering”, Proceedings of the SIAM International Conference on Data Mining (SDM), 623-628, 2007. [pdf]

·       Xiang Zhang and Wei Wang. “Mining Coherent Patterns from Heterogeneous Microarray Data”, Proceedings of the ACM Conference on Information and Knowledge Management (CIKM), 838-839, 2006. [pdf]

·       Emre Karakoc, Meral Ozsoyoglu, Cenk Sahinalp, Murat Tasan, and Xiang Zhang. “Novel Approaches to Biomolecular Sequence Indexing”, IEEE Data Engineering Bulletin, 27 (3), 40-47, 2004. [pdf]

·       Martin Ester and Xiang Zhang. “A Top-Down Method for Mining Most Specific Frequent Patterns in Biological Sequence Data”, Proceedings of the SIAM International Conference on Data Mining (SDM), 90-101, 2004. [pdf]