Peer-reviewed Publications

Google Scholar

* denotes that the author is my student/postdoc; denotes the corresponding author.

I and my research group are very passionate about developing novel yet elegant techniques to solve real-world problems that generate broader impacts. By harnessing large-scale, multi-source, multi-modality data, we discover new research problems, propose novel machine learning (especially deep graph learning and multimodal learning) models, and develop advanced AI techniques for real-world driven applications in cybersecurity and public health. More specifically, we strive to advance knowledge and science in graph learning and trustworthy multimodal learning, bridge AI/ML and cybersecurity concentrating on AI security, large-scale malware detection, and the study of the evolving underground ecosystem, and develop AI and data-driven techniques to combat the opioid crisis and infectious disease outbreaks. Integrating humanity and technology, our long-term goal of research is to advance capabilities and trustworthiness of AI i) to provide state-of-the-art innovations to secure cyberspace for its users, and ii) to improve health and well-being of people around the world.

Our reserach has resulted in over 150 publications on the top-rank venues in the fields of artificial intelligence, machine learning, data mining, and cybersecurity (e.g., ACM CSUR, IEEE TNNLS, IEEE TKDE, IEEE TSMC, SIGKDD, ICDM, CIKM, WWW, NeurIPS, ICLR, ICML, AAAI, IJCAI, USENIX Security, NDSS, ACSAC), including the AAAI-DCAA 2023 Best Paper Runner-Up Award, the SIGKDD 2022 Best Paper Award Shortlist (Research Track), the ACM CIKM 2021 Best Paper Award (Full Paper Track), the ACM CIKM 2021 Best Paper Runner-Up Award (Applied Paper Track), the WWW 2021 Best Paper Award Shortlist, the AICS 2019 Challenge Problem Winner, the SIGKDD 2017 Best Paper Award and SIGKDD 2017 Best Student Paper Award (Applied Data Science Track).

Book Chapters

  • Yanfang Ye. "Intelligent Malware Detection by Applying Data Mining Techniques", In T. Li eds., Data Mining Where Theory Meets Practice, Xiamen University Press, 2013, ISBN 978-7-5615-4294-1.

Journal Publications

  • Chuanbo Hu, Bin Liu, Xin Li, Yanfang Ye, Minglei Yin. "Knowledge-prompted ChatGPT: Enhancing drug trafficking detection on social media", Information & Management, 2024.

  • Chuanbo Hu, Bin Liu, Yanfang Ye, Xin Li. "Fine-grained Classification of Drug Trafficking Based on Instagram Hashtags", Decision Support Systems, 2023.

  • Bo Yan, Cheng Yang, Chuan Shi, Yong Fang, Qi Li, Yanfang Ye, Junping Du. "Graph Mining for Cybersecurity: A Survey", ACM Transactions on Knowledge Discovery from Data (TKDD), 2023.

  • Chunhui Zhang, Hongfu Liu, Jundong Li, Yanfang Ye, Chuxu Zhang. "Mind the Gap: Mitigating the Distribution Gap in Graph Few-shot Learning", Transactions on Machine Learning Research (TMLR), 2023.

  • Xiao Wang, Deyu Bo, Chuan Shi, Shaohua Fan, Yanfang Ye, Phillip Yu. "A Survey on Heterogeneous Graph Embedding: Methods, Techniques, Applications and Sources", IEEE Transactions on Big Data (TBD), 2022.

  • Deqiang Li, Qianmu Li, Yanfang Ye, Shouhuai Xu. "Arms Race in Adversarial Malware Detection: A Survey", ACM Computing Surveys (CSUR), 2021.

  • Chuanbo Hu, Minglei Zhang, Bin Liu, Xin Li, Yanfang Ye. "Identifying Illicit Drug Dealers on Instagram with Large-scale and Multimodal Data Fusion", ACM Transactions on Intelligent Systems and Technology (TIST), 2021.

  • Ruijia Wang, Chuan Shi, Tianyu Zhao, Xiao Wang, Yanfang Ye. "Heterogeneous Information Network Embedding with Adversarial Disentangler", IEEE Transactions on Knowledge and Data Engineering (TKDE), 2021.

  • Deqiang Li, Qianmu Li, Yanfang Ye, Shouhuai Xu. "A Framework for Enhancing Deep Neural Networks against Adversarial Malware", IEEE Transactions on Network Science and Engineering (TNSE), 2021.

  • Liang Zhao, Yuyang Gao, Jieping Ye, Feng Chen, Yanfang Ye, Chang-Tien Lu, Naren Ramakrishnan. "Spatio-temporal Event Forecasting Using Incremental Multi-source Feature Learning", ACM Transactions on Knowledge Discovery from Data (TKDD), 2021.

  • Yiding Zhang, Xiao Wang, Chuan Shi, Xunqiang Jiang, Yanfang Ye. "Hyperbolic Graph Attention Network", IEEE Transactions on Big Data (TBD), 2021.

  • Yanfang Ye (), Yujie Fan*, Shifu Hou*, Yiming Zhang*, Yiyue Qian*, Shiyu Sun*, Qian Peng*, Mingxuan Ju*, Wei Song, Kenneth Loparo. "a-Satellite: An AI-driven System and Benchmark Datasets for Dynamic COVID-19 Risk Assessment in the United States", IEEE Journal of Biomedical and Health Informatics (J-BHI), 2020. MetroLab Innovation of the Month.

  • Jianfei Zhang*, Lifei Chen, Yanfang Ye, Gongde Guo, Rongbo Chen, Alain Vanasse, Shengrui Wang. "Survival Neural Networks for Time-to-event Prediction in Longitudinal Study", Knowledge and Information Systems (KAIS), 2020.

  • Xuan Xu, Yanfang Ye, Xin Li. "Joint Demosaicing and Super-Resolution (JDSR): Network Design and Perceptual Optimization", IEEE Transactions on Computational Imaging (TCI), 2020.

  • Liang Zhao, Feng Chen, Yanfang Ye. "Efficient Learning with Exponentially-Many Conjunctive Precursors for Interpretable Spatial Event Forecasting", IEEE Transactions on Knowledge and Data Engineering (TKDE), 2019.

  • Qingzhe Li, Amir Alipour-Fanid, Martin Slawski, Yanfang Ye, Lingfei Wu, Kai Zeng, Liang Zhao. "Large-scale Cost-aware Classification Using Feature Computational Dependencies", IEEE Transactions on Knowledge and Data Engineering (TKDE), 2019.

  • Junxiang Wang, Liang Zhao, Yanfang Ye, Yuji Zhang. "Adverse Event Detection by Integrating Twitter Data and VAERS", Journal of Biomedical Semantics, 9(19), 2018.

  • Yanfang Ye, Tao Li, Donald Adjeroh, S. Sitharama Iyengar. "A Survey on Malware Detection Using Data Mining Techniques", ACM Computing Surveys (ACM CSUR), Vol. 50, Issue 3, Article No. 41, 2017.

  • Yanfang Ye (), Lingwei Chen*, Shifu Hou*, William Hardy*, Xin Li. "DeepAM: A Heterogeneous Deep Learning Framework for Intelligent Malware Detection", Knowledge and Information Systems (KAIS), Vol. PP (52): 1~21, 2017.

  • Gongde Guo, Lifei Chen, Yanfang Ye, Qingshan Jiang. "Cluster Validation Method for Determining the Number of Clusters in Categorical Sequences", IEEE Transactions on Neural Networks and Learning Systems, Vol. PP (99): 1-13, 2016.

  • Ming Ni, Tao Li, Qianmu Li, Hong Zhang, Yanfang Ye, Qingshan Jiang. "FindMal: A File-to-file Social Network Based Malware Detection Framework", Knowledge-Based Systems, 112: 142-151, 2016.

  • Yujie Fan*, Yanfang Ye, Lifei Chen. "Malicious Sequential Pattern Mining for Automatic Malware Detection", Expert Systems with Applications, Vol. 52, pp. 16~25, 2016.

  • Madhuri Siddula*, Fei Dai, Yanfang Ye, Jianping Fan. "Classifying Construction Site Photos for Roof Detection: A Machine-Learning Method towards Automated Measurement of Safety Performance on Roof Sites", Construction Innovation, 16(3), pp. 368~389, 2016.

  • Yanfang Ye (), Tao Li, Haiyin Shen. "Soter: Smart Bracelets for Children's Safety", ACM Transactions on Intelligent Systems and Technology , Vol.6, No. 4, Article 46, 2015.

  • Lifei Chen, Yanfang Ye, Gongde Guo, Jianping Zhu. "Kernel-based linear classification on categorical data", Soft Computing, pp. 1~13, 2015.

  • Weiwei Zhuang, Yanfang Ye, Yong Chen, Tao Li. "Ensemble Clustering for Internet Security Applications", IEEE Transactions on Systems, Man and Cybernetics-Part C: Applications and Reviews, Vol 42, pp. 1784~1796, 2012.

  • Weiwei Zhuang, Yanfang Ye, Tao Li, Qingshan Jiang. "Intelligent phishing website detection using classification ensemble", Systems Engineering - Theory & Practice, Vol. 31, issue (10): 2008-2020, 2011.

  • Yanfang Ye, Tao Li, Qingshan Jiang, Youyu Wang. "CIMDS: Adapting post-processing techniques of associative classification for malware detection system", IEEE Transactions on Systems, Man and Cybernetics-Part C: Applications and Reviews, Vol 40, pp. 298~307, 2010.

  • Yanfang Ye, Lifei Chen, Dingding Wang, Tao Li, Qingshan Jiang, Min Zhao. "SBMDS: an interpretable string based malware detection system using SVM ensemble with bagging", Journal in Computer Virology, Vol 5, pp. 283~293, 2009.

  • Yanfang Ye, Tao Li, Kai Huang, Qingshan Jiang, Yong Chen. "Hierarchical Associative Classifier (HAC) for Malware Detection from the Large and Imbalanced Gray List", Journal of Intelligent Information Systems, Vol 35, pp. 1~20, 2009.

  • Weiwei Zhuang, Yanfang Ye, Qingshan Jiang, Zhixue Han. "Application of Incremental Associative Classification Method in Malware Detection", Computer Engineering, 35 (4): 159-161, 2009.

  • Yanfang Ye, Dingding Wang, Tao Li, Dongyi Ye, Qingshan Jiang. "An Intelligent PE-Malware Detection System Based on Association Mining", Journal in Computer Virology, Vol 4, pp. 323~334, 2008.

Conference Publications

  • Shang Ma*, Chaoran Chen*, Shao Yang, Shifu Hou, Toby Jia-jun Li, Xusheng Xiao, Tao Xie, Yanfang Ye (). "Careful About What App Promotion Ads Recommend! Predict and Explain Malware Promotion through App Promotion Graph", The Network and Distributed System Security Symposium (NDSS), 2025.

  • Yiyue Qian*, Tianyi Ma*, Chuxu Zhang, Yanfang Ye (). "Adaptive Graph Enhancement for Imbalanced Multi-relation Graph Learning", ACM International Conference on Web Search and Data Mining (WSDM), 2025. (17.3% acceptance rate)

  • Zehong Wang*, Zheyuan Zhang*, Nitesh V Chawla, Chuxu Zhang, Yanfang Ye (). "Training MLPs on Graphs without Supervision", ACM International Conference on Web Search and Data Mining (WSDM), 2025. (17.3% acceptance rate)

  • Zheyuan Zhang*, Zehong Wang*, Tianyi Ma*, Varun Sameer Taneja*, Sofia Nelson*, Nhi Ha Lan Le, Keerthiram Murugesan, Mingxuan Ju*, Nitesh V Chawla, Chuxu Zhang, Yanfang Ye (). "MOPI-HFRS: A Multi-objective Personalized Health-aware Food Recommendation System with LLM-enhanced Interpretation", The 31st SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2025. (22% acceptance rate in ADS Track)

  • Zehong Wang*, Zheyuan Zhang*, Nitesh V Chawla, Chuxu Zhang, Yanfang Ye (). "Graph Foundation Model with Transferable Tree Vocabulary", The Conference on Neural Information Processing Systems (NeurIPS), 2024. (25.8% acceptance rate)

  • Mingxuan Ju*, William Shiao, Zhichun Guo, Yanfang Ye (), Yozen Liu, Neil Shah, Tong Zhao. "How Does Message Passing Improve Collaborative Filtering?", The Conference on Neural Information Processing Systems (NeurIPS), 2024. (25.8% acceptance rate)

  • Yiyue Qian*, Tianyi Ma*, Chuxu Zhang, Yanfang Ye (). "Dual-level Hypergraph Contrastive Learning with Adaptive Temperature", The ACM Web Conference (WWW), 2024. (20.2% acceptance rate)

  • Qianlong Wen*, Zhongyu Ouyang*, Chunhui Zhang, Yiyue Qian*, Chuxu Zhang, Yanfang Ye (). "GCVR: Reconstruction from Cross-View Enable Sufficient and Robust Graph Contrastive Learning", The 40th Conference on Uncertainty in Artificial Intelligence (UAI), 2024. (27% acceptance rate)

  • Zehong Wang*, Zheyuan Zhang*, Chuxu Zhang, Yanfang Ye (). "Subgraph Pooling: Tackling Negative Transfer on Graphs", The 33rd International Joint Conference on Artificial Intelligence (IJCAI), 2024.

  • Zheyuan Zhang*, Zehong Wang*, Shifu Hou*, Evan Hall*, Landon Bachman*, Jasmine White*, Vincent Galassi*, Nitesh V Chawla, Chuxu Zhang, Yanfang Ye (). "Diet-ODIN: A Novel Framework for Opioid Misuse Detection with Interpretable Dietary Patterns", The 30th SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2024. (20% acceptance rate in ADS Track)

  • Xiangchi Yuan, Yijun Tian, Chunhui Zhang, Yanfang Ye, Chuxu Zhang. "Graph Cross Supervised Learning via Generalized Knowledge", The 30th SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2024. (20% acceptance rate in Research Track)

  • Zhongyu Ouyang*, Chunhui Zhang, Shifu Hou*, Shang Ma*, Chaoran Chen*, Toby Li, Xusheng Xiao, Chuxu Zhang, Yanfang Ye (). "Completing the App Promotion Graph with Symbolic Prompting", European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database (ECML-PKDD), 2024. (24.5% acceptance rate in ADS Track)

  • Chaoran Chen*, Weijun Li, Wenxin Song, Yanfang Ye, Yaxing Yao, Toby Li. "An Empathy-Based Sandbox Approach to Bridge the Privacy Gap among Attitudes, Goals, Knowledge, and Behaviors", The ACM Conference on Human Factors in Computing Systems (CHI), 2024. (29% acceptance rate)

  • Chaoran Chen*, Bingsheng Yao, Yanfang Ye, Dakuo Wang, Toby Jia-Jun Li. "Evaluating the LLM Agents for Simulating Humanoid Behavior", The First Workshop on Human-Centered Evaluation and Auditing of Language Models (CHI Workshop HEAL), 2024.

  • Xiangchi Yuan, Chunhui Zhang, Yijun Tian, Yanfang Ye, Chuxu Zhang. "Mitigating Severe Robustness Degradation on Graphs", The Twelfth International Conference on Learning Representations (ICLR), 2024. (31% acceptance rate)

  • Zhongyu Ouyang*, Chunhui Zhang, Shifu Hou*, Chuxu Zhang, Yanfang Ye (). "How to Improve Representation Alignment and Uniformity in Graph-based Collaborative Filtering?" Proceedings of the International AAAI Conference on Web and Social Media (ICWSM), 2024. (11.6% acceptance rate)

  • Qianlong Wen*, Mingxuan Ju*, Zhongyu Ouyang*, Chuxu Zhang, Yanfang Ye (). "From Coarse to Fine: Enable Comprehensive Graph Self-supervised Learning with Multi-granular Semantic Ensemble", The 41st International Conference on Machine Learning (ICML), 2024. (27.5% acceptance rate)

  • Lichao Sun, Yue Huang, Haoran Wang, Siyuan Wu, Qihui Zhang, Chujie Gao, Yixin Huang, Wenhan Lyu, Yixuan Zhang, Xiner Li, Zhengliang Liu, Yixin Liu, Yijue Wang, Zhikun Zhang, Bhavya Kailkhura, Caiming Xiong, Chao Zhang, Chaowei Xiao, Chunyuan Li, Eric Xing, Furong Huang, Hao Liu, Heng Ji, Hongyi Wang, Huan Zhang, Huaxiu Yao, Manolis Kellis, Marinka Zitnik, Meng Jiang, Mohit Bansal, James Zou, Jian Pei, Jian Liu, Jianfeng Gao, Jiawei Han, Jieyu Zhao, Jiliang Tang, Jindong Wang, John Mitchell, Kai Shu, Kaidi Xu, Kai-Wei Chang, Lifang He, Lifu Huang, Michael Backes, Neil Zhenqiang Gong, Philip S Yu, Pin-Yu Chen, Quanquan Gu, Ran Xu, Rex Ying, Shuiwang Ji, Suman Jana, Tianlong Chen, Tianming Liu, Tianyi Zhou, Willian Wang, Xiang Li, Xiangliang Zhang, Xiao Wang, Xing Xie, Xun Chen, Xuyu Wang, Yan Liu, Yanfang Ye, Yinzhi Cao, Yue Zhao. "TrustLLM: Trustworthiness in Large Language Models", The 41st International Conference on Machine Learning (ICML), 2024. (26.2% acceptance rate for position papers)

  • Mingxuan Ju*, Tong Zhao, Wenhao Yu, Neil Shah, Yanfang Ye (). "GraphPatcher: Mitigating Degree Bias for Graph Neural Networks via Test-time Node Patching", Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS), 2023. (26.1% acceptance rate)

  • Qianlong Wen*, Jiazheng Li, Chuxu Zhang, Yanfang Ye (). "A Multi-Modality Framework for Drug-Drug Interaction Prediction by Harnessing Multi-source Data", International Conference on Information and Knowledge Management (CIKM), 2023. (24% acceptance rate)

  • Tianyi Ma*, Yiyue Qian*, Chuxu Zhang, Yanfang Ye (). "Hypergraph Contrastive Learning for Drug Trafficking Community Detection", 23rd IEEE International Conference on Data Mining (ICDM), 2023. (19.9% acceptance rate)

  • Mingxuan Ju*, Yujie Fan*, Chuxu Zhang, Yanfang Ye (). "Let Graph be the Go Board: Gradient-free Node Injection Attack for Graph Neural Networks via Reinforcement Learning", 37th AAAI Conference on Artificial Intelligence (AAAI), 2023. (19.6% acceptance rate)

  • Chunhui Zhang, Yijun Tian, Qianlong Wen*, Zhongyu Ouyang*, Yanfang Ye, Chuxu Zhang. "Unifying Data-Model Sparsity for Class-Imbalanced Graph Representation Learning", The First Workshop on DL-Hardware Co-Design for AI Acceleration (DCAA) collocated with the 37th AAAI Conference on Artificial Intelligence, 2023. AAAI-DCAA 2023 Best Paper Runner-Up Award.

  • Shifu Hou*, Lingwei Chen*, Mingxuan Ju*, Yanfang Ye (). "Leveraging Comment Retrieval for Code Summarization", The 45th European Conference on Information Retrieval (ECIR), 2023. (27% acceptance rate for short paper)

  • Jianan Zhao*, Qianlong Wen*, Mingxuan Ju*, Chuxu Zhang, Yanfang Ye (). "Self-Supervised Graph Structure Refinement for Graph Neural Networks", The 16th ACM International WSDM Conference (WSDM), 2023. (17.8% acceptance rate)

  • Chunhui Zhang, Chao Huang, Yijun Tian, Qianlong Wen*, Zhongyu Ouyang*, Youhuan Li, Yanfang Ye, Chuxu Zhang. "When Sparsity Meets Contrastive Models: Less Graph Data Can Bring Better Class-Balanced Representations", Fortieth International Conference on Machine Learning (ICML), 2023. (27.9% acceptance rate)

  • Mingxuan Ju*, Tong Zhao, Qianlong Wen*, Wenhao Yu, Neil Shah, Yanfang Ye (), Chuxu Zhang. "Multi-task Self-supervised Graph Neural Networks Enable Stronger Task Generalization", International Conference on Learning Representations (ICLR), 2023. (31.8% acceptance rate)

  • Chunhui Zhang, Yijun Tian, Mingxuan Ju*, Zheyuan Liu, Yanfang Ye, Nitesh Chawla, Chuxu Zhang. "Chasing All-Round Graph Representation Robustness: Model, Training, and Optimization", International Conference on Learning Representations (ICLR), 2023. (31.8% acceptance rate)

  • Zheyuan Liu, Chunhui Zhang, Yijun Tian, Erchi Zhang, Chao Huang, Yanfang Ye, Chuxu Zhang. "G-FAME: Fair Graph Representation Learning via Diverse Mixture of Experts", The Web Conference (WWW), 2023. (19.2% acceptance rate)

  • Qianlong Wen*, Zhongyu Ouyang*, Jianfei Zhang*, Yiyue Qian*, Yanfang Ye (), Chuxu Zhang. "Disentangled Heterogeneous Dynamic Graph Learning for Opioid Overdose Prediction", International Conference on Knowledge Discovery and Data Mining (ACM SIGKDD), 2022. SIGKDD 2022 Best Paper Award Shortlist (Research Track). (15% acceptance rate)

  • Yiyue Qian*, Yiming Zhang*, Qianlong Wen*, Yanfang Ye (), Chuxu Zhang. "Rep2Vec: Repository Embedding via Heterogeneous Graph Adversarial Contrastive Learning", International Conference on Knowledge Discovery and Data Mining (ACM SIGKDD), 2022. (15% acceptance rate)

  • Mingxuan Ju*, Shifu Hou*, Yujie Fan*, Jianan Zhao*, Yanfang Ye (), Liang Zhao. "Adaptive Kernel Graph Neural Network", 36th AAAI Conference on Artificial Intelligence (AAAI), 2022. (15% acceptance rate)

  • Yuanqi Du, Xiaojie Guo, Hengning Cao, Yanfang Ye, Liang Zhao. "Disentangled Spatiotemporal Graph Generative Model", 36th AAAI Conference on Artificial Intelligence (AAAI), 2022. (15% acceptance rate)

  • Yiyue Qian*, Chunhui Zhang, Yiming Zhang*, Qianlong Wen*, Yanfang Ye (), Chuxu Zhang. "Co-Modality Graph Contrastive Learning for Imbalanced Node Classification", Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS), 2022. (25.6% acceptance rate)

  • Shiyu Wang, Xiaojie Guo, Xuanyang Lin, Bo Pan, Yuanqi Du, Yinkai Wang, Yanfang Ye, Ashley Petersen, Austin Leitgeb, Saleh Alkhalifa, Kevin Minbiole, Bill Wuest, Amarda Shehu, Liang Zhao. "Multi-objective Deep Data Generation with Correlated Property Control", Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS), 2022. (25.6% acceptance rate)

  • Mingxuan Ju*, Wenhao Yu, Tong Zhao, Chuxu Zhang, Yanfang Ye (). "Grape: Knowledge Graph Enhanced Passage Reader for Open-domain Question Answering", Conference on Empirical Methods in Natural Language Processing (EMNLP), 2022.

  • Chuxu Zhang, Kaize Ding, Jundong Li, Xiangliang Zhang, Yanfang Ye, Nitesh V Chawla, Huan Liu. "Adapting Meta Knowledge with Heterogeneous Information Network for COVID-19 Themed Malicious Repository Detection", 31st International Joint Conference on Artificial Intelligence (IJCAI), 2022. (18% acceptance rate, Survey Track)

  • Jianfei Zhang*, Ai-Te Kuo, Jianan Zhao*, Qianlong Wen*, Erin Winstanley, Chuxu Zhang, Yanfang Ye (). "Rx-refill Graph Neural Network to Reduce Drug Overprescribing Risks", 31st International Joint Conference on Artificial Intelligence (IJCAI), 2022. (Sister Conferences Best Papers)

  • Yujie Fan*, Mingxuan Ju*, Chuxu Zhang, Yanfang Ye (). "Heterogeneous Temporal Graph Neural Network", SIAM International Conference on Data Mining (SIAM SDM), 2022. (27.8% acceptance rate)

  • Yiming Zhang*, Yiyue Qian*, Yanfang Ye (), Chuxu Zhang. "Adapting Distilled Knowledge for Few-Shot Relation Reasoning over Knowledge Graphs", SIAM International Conference on Data Mining (SIAM SDM), 2022. (27.8% acceptance rate)

  • Pengcheng Fang, Peng Gao, Changlin Liu, Erman Ayday, Kangkook Jee, Ting Wang, Yanfang Ye, Zhuotao Liu, Xusheng Xiao. "Back-Propagating System Dependency Impact for Attack Investigation", Thirty-first USENIX Security Symposium (USENIX Security), 2022. (18.1% acceptance rate)

  • Shao Yang, Yuehan Wang, Yuan Yao, Haoyu Wang, Yanfang Ye, Xusheng Xiao. "DescribeCtx: Context-Aware Description Synthesis for Sensitive Behaviors in Mobile Apps", 44th International Conference on Software Engineering (ICSE), 2022. (26% accept rate)

  • Yiyue Qian*, Yiming Zhang*, Nitesh V Chawla, Yanfang Ye (), Chuxu Zhang. "Malicious Repositories Detection with Adversarial Heterogeneous Graph Contrastive Learning", International Conference on Information and Knowledge Management (CIKM), 2022. (23.3% acceptance rate)

  • Chunhui Zhang, Chao Huang, Youhuan Li, Xiangliang Zhang, Yanfang Ye, Chuxu Zhang. "Look Twice as Much as You Say: Scene Graph Contrastive Learning for Self-Supervised Image Caption Generation", International Conference on Information and Knowledge Management (CIKM), 2022. (23.3% acceptance rate)

  • Shifu Hou*, Lingwei Chen, Yanfang Ye (). "Summarizing Source Code from Structure and Context", IEEE World Congress on Computational Intelligence (IEEE WCCI), 2022.

  • Jianfei Zhang*, Ai-Te Kuo, Jianan Zhao*, Qianlong Wen*, Erin Winstanley, Chuxu Zhang, Yanfang Ye (). "RxNet: Rx-refill Networks for Overprescribing Prediction", International Conference on Information and Knowledge Management (CIKM), 2021. CIKM 2021 Best Paper Award. (21.7% acceptance rate for full paper, 1st out of 1251)

  • Chuanbo Hu, Minglei Yin, Bin Liu, Xin Li, Yanfang Ye. "Detection of Illicit Drug Trafficking Events on Instagram: A Deep Multimodal Multi-label Learning Approach", International Conference on Information and Knowledge Management (CIKM), 2021. CIKM 2021 Best Paper Runner-Up Award. (24% acceptance rate for applied track, 2nd out of 290)

  • Mingxuan Ju*, Wei Song, Shiyu Sun*, Yanfang Ye (), Yujie Fan*, Shifu Hou*, Kenneth Loparo, Liang Zhao. "Dr.Emotion: Disentangled Representation Learning for Emotion Analysis on Social Media to Improve Community Resilience in the COVID-19 Era and Beyond", The Web Conference (WWW), 2021. WWW 2021 Best Paper Award Shortlist. (20.6% acceptance rate)

  • Yujie Fan*, Mingxuan Ju*, Shifu Hou*, Yanfang Ye (), Wenqiang Wan, Kui Wang, Yinming Mei, Qi Xiong. "Heterogeneous Temporal Graph Transformer: An Intelligent System for Evolving Android Malware Detection", International Conference on Knowledge Discovery and Data Mining (ACM SIGKDD), 2021. (19.6% acceptance rate)

  • Yiyue Qian*, Yiming Zhang*, Yanfang Ye (), Chuxu Zhang. "Adapting Meta Knowledge with Heterogeneous Information Network for COVID-19 Themed Malicious Repository Detection", 30th International Joint Conference on Artificial Intelligence (IJCAI), 2021. (13.9% acceptance rate)

  • Jianan Zhao*, Xiao Wang, Chuan Shi, Binbin Hu, Guojie Song, Yanfang Ye. "Heterogeneous Graph Structure Learning for Graph Neural Networks", 35th AAAI Conference on Artificial Intelligence (AAAI), 2021. (21% acceptance rate)

  • Shifu Hou*, Yujie Fan*, Mingxuan Ju*, Yanfang Ye (), Wenqiang Wan, Kui Wang, Yinming Mei, Qi Xiong, Fudong Shao. "Disentangled Representation Learning in Heterogeneous Information Network for Large-scale Android Malware Detection in the COVID-19 Era and Beyond", 35th AAAI Conference on Artificial Intelligence (AAAI), 2021. (21% acceptance rate)

  • Chao Huang, Huance Xu, Yong Xu, Peng Dai, Lianghao Xia, Mengyin Lu, Liefeng Bo, Hao Xing, Xiaoping Lai, Yanfang Ye. "Knowledge-aware Coupled Graph Neural Network for Social Recommendation", 35th AAAI Conference on Artificial Intelligence (AAAI), 2021. (21% acceptance rate)

  • Yiyue Qian*, Yiming Zhang*, Yanfang Ye (), Chuxu Zhang. "Distilling Meta Knowledge on Heterogeneous Graph for Illicit Drug Trafficker Detection on Social Media", Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS), 2021. (26% acceptance rate)

  • Jianan Zhao*, Qianlong Wen*, Shiyu Sun*, Yanfang Ye (), Chuxu Zhang. "Multi-View Self-Supervised Heterogeneous Graph Embedding", European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD), 2021. (21% acceptance rate)

  • Lingwei Chen, Yujie Fan*, Yanfang Ye. "Adversarial Reprogramming of Pretrained Neural Networks for Fraud Detection", International Conference on Information and Knowledge Management (CIKM), 2021. (28% acceptance rate for short paper)

  • Fei Shao, Rui Xu, Wasif Haque, Jingwei Zu, Ying Zhang, Wei Yang, Yanfang Ye, Xusheng Xiao. "WebEvo: TamingWeb Application Evolution via Detecting Semantic Structure Change", International Symposium on Software Testing and Analysis (ISSTA), 2021. (21.9% acceptance rate)

  • Tianxi Ji, Pan Li, Emre Yilmaz, Erman Ayday, Yanfang Ye, Jinyuan Sun. "Differentially Private Binary- and Matrix-Valued Data Query: An XOR Mechanism", 47th International Conference on Very Large Data Bases (VLDB), 2021.

  • Long Phan*, Hieu Tran, Daniel Le*, Hieu Nguyen, James Anibal, Alec Peltekian*, Yanfang Ye (). "CoTexT: Multi-task Learning with Code-Text Transformer", NLP4Prog Workshop (NLP4Prog), 2021.

  • Yujie Fan*, Yanfang Ye (), Qian Peng*, Jianfei Zhang*, Yiming Zhang*, Xusheng Xiao, Chuan Shi, Qi Xiong, Fudong Shao, Liang Zhao. "Metagraph Aggregated Heterogeneous Graph Neural Network for Illicit Traded Product Identification in Underground Market", IEEE International Conference on Data Mining (ICDM), 2020. (full paper acceptance rate of 9.8%)

  • Yiming Zhang*, Yiyue Qian*, Yujie Fan*, Yanfang Ye (), Xin Li, Qi Xiong, Fudong Shao. "dStyle-GAN: Generative Adversarial Network based on Writing and Photography Styles for Drug Identification in Darknet Markets", Annual Computer Security Applications Conference (ACSAC), 2020. (23% acceptance rate)

  • Jianan Zhao, Xiao Wang, Chuan Shi, Zekuan Liu, Yanfang Ye. "Network Schema Preserved Heterogeneous Information Network Embedding", 29th International Joint Conference on Artificial Intelligence (IJCAI), 2020. (12.6% acceptance rate)

  • Xiaojie Guo, Liang Zhao, Zhao Qin, Lingfei Wu, Amarda Shehu, Yanfang Ye. "Node-Edge Co-disentangled Representation Learning for Attributed Graph Generation", International Conference on Knowledge Discovery and Data Mining (ACM SIGKDD), 2020. (16.9% acceptance rate)

  • Yanfang Ye (), Yujie Fan*, Shifu Hou*, Yiming Zhang*, Yiyue Qian*, Shiyu Sun*, Qian Peng*, Mingxuan Ju*, Wei Song, Kenneth Loparo. "Community Mitigation: A Data-driven System for COVID-19 Risk Assessment in a Hierarchical Manner", International Conference on Information and Knowledge Management (CIKM), 2020. (21% acceptance rate)

  • Yiming Zhang*, Yujie Fan*, Shifu Hou*, Yanfang Ye (), Xusheng Xiao, Pan Li, Chuan Shi, Liang Zhao, Shouhuai Xu. "Cyber-guided Deep Neural Network for Malicious Repository Detection in GitHub", IEEE International Conference on Knowledge Graph (ICKG), 2020.

  • Yanfang Ye (), Shifu Hou*, Lingwei Chen*, Jingwei Lei, Wenqiang Wan, Jiabin Wang, Qi Xiong, Fudong Shao. "Out-of-sample Node Representation Learning for Heterogeneous Graph in Real-time Android Malware Detection", 28th International Joint Conference on Artificial Intelligence (IJCAI), 2019. (17.9% acceptance rate)

  • Yujie Fan*, Yiming Zhang*, Shifu Hou*, Lingwei Chen*, Yanfang Ye (), Chuan Shi, Liang Zhao, Shouhuai Xu. "iDev: Enhancing Social Coding Security by Cross-platform User Identification Between GitHub and Stack Overflow", 28th International Joint Conference on Artificial Intelligence (IJCAI), 2019. (17.9% acceptance rate)

  • Yiming Zhang*, Yujie Fan*, Wei Song, Shifu Hou*, Yanfang Ye (), Xin Li, Liang Zhao, Chuan Shi, Jiabin Wang, Qi Xiong. "Your Style Your Identity: LeveragingWriting and Photography Styles for Drug Trafficker Identification in Darknet Markets over Attributed Heterogeneous Information Network", The Web Conference (WWW), 2019. (20% acceptance rate for short paper)

  • Xiao Wang, Houye Ji, Chuan Shi, Bai Wang, Peng Cui, Yanfang Ye. "Heterogeneous Graph Attention Network", The Web Conference (WWW), 2019. (18% acceptance rate for regular paper)

  • Yuyang Gao, Liang Zhao, Lingfei Wu, Yanfang Ye, Hui Xiong, Chaowei Yang. "Incomplete Label Multi-task Deep Learning for Spatio-temporal Event Subtype Forecasting", P33rd AAAI Conference on Artificial Intelligence (AAAI), 2019. (16.7% acceptance rate)

  • Deqiang Li, Qianmu Li, Yanfang Ye, Shouhuai Xu. "Enhancing Robustness of Deep Neural Networks Against Adversarial Malware Samples: Principles, Framework, and Application to AICS'2019 Challenge", AAAI Workshop on Artificial Intelligence for Cyber Security (AICS), 2019. AICS 2019 Challenge Problem Winner.

  • Qingzhe Li, Liang Zhao, Yi-Ching Lee, Yanfang Ye, Jessica Lin, Lingfei Wu. "Contrast Feature Dependency Pattern Mining for Controlled Experiments with Application to Driving Behavior", 19th IEEE International Conference on Data Mining (ICDM), 2019. (18.5% acceptance rate)

  • Shifu Hou*, Yujie Fan*, Yiming Zhang*, Yanfang Ye (), Jingwei Lei, Wenqiang Wan, Jiabin Wang, Qi Xiong and Fudong Shao. "aCyber: Enhancing Robustness of Android Malware Detection System against Adversarial Attacks on Heterogeneous Graph based Model", International Conference on Information and Knowledge Management (CIKM), 2019. (19.4% acceptance rate)

  • Yiming Zhang*, Yujie Fan*, Yanfang Ye (), Liang Zhao, Chuan Shi. "Key Player Identification in Underground Forums over Attributed Heterogeneous Information Network Embedding Framework", International Conference on Information and Knowledge Management (CIKM), 2019. (19.4% acceptance rate)

  • Yuanfu Lu, Xiao Wang, Chuan Shi, Philip Yu, Yanfang Ye. "Temporal Network Embedding with Micro- and Macro-dynamics", International Conference on Information and Knowledge Management (CIKM), 2019. (19.4% acceptance rate)

  • Yuyan Zheng, Chuan Shi, Xiangnan Kong, Yanfang Ye. "Author Set Identification via Quasi-Clique Discovery", International Conference on Information and Knowledge Management (CIKM), 2019. (19.4% acceptance rate)

  • Lingwei Chen*, Shifu Hou*, Yanfang Ye (), Thirimachos Bourlai, Shouhuai Xu, Liang Zhao. "iTrustSO: An Intelligent System for Automatic Detection of Insecure Code Snippets in Stack Overflow", Proceedings of International conference on Advances in Social Network Analysis and Mining (ASONAM), 2019.

  • Yujie Fan*, Shifu Hou*, Yiming Zhang*, Yanfang Ye (), Melih Abdulhayoglu. "Gotcha - Sly Malware! Scorpion: A Metagraph2vec Based Malware Detection System", Proceedings of ACM International Conference on Knowledge Discovery and Data Mining (ACM SIGKDD), 2018. (22.5% acceptance rate)

  • Yujie Fan*, Yiming Zhang*, Yanfang Ye (), Xin Li. "Automatic Opioid User Detection from Twitter: Transductive Ensemble Built on Different Meta-graph Based Similarities over Heterogeneous Information Network", 27th International Joint Conference on Artificial Intelligence (IJCAI), 2018. (20.5% acceptance rate)

  • Shifu Hou*, Yanfang Ye (), Yangqiu Song, Melih Abdulhayoglu. "Make Evasion Harder: An Intelligent Android Malware Detection System", 27th International Joint Conference on Artificial Intelligence (IJCAI), 2018. (20.5% acceptance rate)

  • Junxiang Wang, Liang Zhao, Yanfang Ye. "Semi-supervised Multi-instance Learning for Flu Shot Adverse Event Detection", IEEE international conference on Big Data (BigData), 2018. (18.9% acceptance rate)

  • Yanfang Ye (), Shifu Hou*, Lingwei Chen*, Xin Li, Liang Zhao, Shouhuai Xu, Jiabin Wang, Qi Xiong. "ICSD: An Automatic System for Insecure Code Snippet Detection in Stack Overflow over Heterogeneous Information Network", Annual Computer Security Applications Conference (ACSAC), 2018. (20.1% acceptance rate)

  • Lingwei Chen*, Shifu Hou*, Yanfang Ye (), Shouhuai Xu. "DroidEye: Fortifying Security of Learning-based Classifier against Adversarial Android Malware Attacks", Proceedings of International conference on Advances in Social Network Analysis and Mining (ASONAM), 2018.

  • Yiming Zhang*, Yujie Fan*, Shifu Hou*, Jian Liu*, Yanfang Ye (), Thirimachos Bourlai. "iDetector: Automate Underground Forum Analysis Based on Heterogeneous Information Network", Proceedings of International conference on Advances in Social Network Analysis and Mining (ASONAM), 2018.

  • Yiming Zhang*, Yujie Fan*, Yanfang Ye (), Xin Li, Erin L. Winstanley. "Utilizing Social Media to Combat Opioid Addiction Epidemic: Automatic Detection of Opioid Users from Twitter", The Thirty-Second AAAI Conference on Artificial Intelligence Workshops (AAAI Workshop), 2018.

  • Shifu Hou*, Yanfang Ye (), Yangqiu Song, Melih Abdulhayoglu. "HinDroid: An Intelligent Android Malware Detection System Based on Structured Heterogeneous Information Network", Proceedings of ACM International Conference on Knowledge Discovery and Data Mining (ACM SIGKDD), 2017. SIGKDD 2017 Best Paper Award and SIGKDD 2017 Best Student Paper Award (Applied Data Science Track). (9.2% acceptance rate for oral, 1st out of 396)

  • Lingwei Chen*, Yanfang Ye (), Thirimachos Bourlai. "Adversarial Machine Learning in Malware Detection: Arms Race between Evasion Attack and Defense", IEEE European Intelligence and Security Informatics Conference (EISIC), 2017. IEEE EISIC 2017 Best Paper Award. (~25% acceptance rate)

  • Lingwei Chen*, Shifu Hou*, Yanfang Ye (). "SecureDroid: Enhancing Security of Machine Learning-based Detection against Adversarial Android Malware Attacks", Annual Computer Security Applications Conference (ACSAC), 2017. (19.7% acceptance rate)

  • Yujie Fan*, Yiming Zhang*, Yanfang Ye (), Xin Li, Wanhong Zheng. "Social Media for Opioid Addiction Epidemiology: Automatic Detection of Opioid Addicts from Twitter and Case Studies", ACM International Conference on Information and Knowledge Management (CIKM), 2017. (20% acceptance rate)

  • Yiming Zhang*, Yujie Fan*, Yanfang Ye (), Xin Li, Wanhong Zheng. "Detecting Opioid Users from Twitter and Understanding their Perceptions toward MAT", IEEE International Conference on Data Mining Workshops (ICDMW), 2017.

  • Lingwei Chen*, Yanfang Ye (). "SecMD: Make Machine Learning More Secure Against Adversarial Malware Attacks", Australasian Joint Conference on Artificial Intelligence (AI), 2017.

  • Shifu Hou*, Aaron Saas*, Lingwei Chen, Yanfang Ye (), Thirimachos Bourlai. "Deep Neural Networks for Automatic Android Malware Detection", International conference on Advances in Social Network Analysis and Mining (ASONAM), 2017.

  • Shifu Hou*, Lingwei Chen*, Yanfang Ye (), Lifei Chen. "Deep Analysis and Utilization of Malware's Social Relation Network for its Detection", Proceedings of International Conference on Web-Age Information Management (WAIM), 2017.

  • Lingwei Chen*, Shifu Hou*, Yanfang Ye (), Lifei Chen. "An Adversarial Machine Learning Model against Android Malware Evasion Attacks", Proceedings of International Conference on Web-Age Information Management (WAIM) , 2017.

  • Shifu Hou*, Aaron Saas*, Yanfang Ye (), Lifei Chen. "Deep4MalDroid: A Deep Learning Framework for Android Malware Detection Based on Linux Kernel System Call Graphs", IEEE/WIC/ACM International Conference on Web Intelligence Workshops (WIW), 2016.

  • Abu Hasnat Mohammad Rubaiyat, Tanjin Taher Toma, Masoumeh Kalantari-Khandani, Syed Ashiqur Rahman, Lingwei Chen*, Yanfang Ye (), Christopher S. Pan. "Automatic Detection of Helmet Uses for Construction Safety", IEEE/WIC/ACM International Conference on Web Intelligence Workshops (WIW), 2016.

  • Shifu Hou*, Aaron Saas*, Yanfang Ye (), Lifei Chen. "DroidDelver: An Android Malware Detection System Using Deep Belief Network Based on API Call Blocks", Proceedings of International Conference on Web-Age Information Management(WAIM), 2016.

  • William Hardy*, Lingwei Chen*, Shifu Hou*, Yanfang Ye (), Xin Li. "DL4MD: A Deep Learning Framework for Intelligent Malware Detection", International Conference on Data Mining (DMIN), 2016.

  • Madhuri Siddula*, Fei Dai, Yanfang Ye, Jianping Fan. "Learning in Unordered and Static Daily Construction Site Photos for Roof Detection: A Step toward Automated Safety Performance Monitoring for Work on Rooftops", The 16th International Conference on Computing in Civil and Building Engineering (ICCCBE), 2016.

  • Madhuri Siddula*, Fei Dai, Yanfang Ye, Jianping Fan. "Unsupervised Feature Learning for Objects of Interest Detection in Cluttered Construction Roof Site Images", International Conference on Sustainable Design, Engineering and Construction (ICSDEC), 2016.

  • Lingwei Chen*, William Hardy*, Yanfang Ye (), Tao Li. "Analyzing File-to-File Relation Network in Malware Detection", Web Information System Engineering (WISE), pp. 415~430, 2015.

  • Shifu Hou*, Lifei Chen, Egemen Tas, Igor Demihovskiy, Yanfang Ye (). "Cluster-Oriented Ensemble Classifiers for Malware Detection", IEEE International Conference on Sematic Computing (IEEE ICSC), pp. 189~196, 2015.

  • Lingwei Chen*, Tao Li, Melih Abdulhayoglu, Yanfang Ye (). "Malware Detection Based on File Relation Graphs", IEEE International Conference on Sematic Computing (IEEE ICSC), pp. 85~92, 2015 (Invited Paper).

  • Yanfang Ye, Tao Li, Shenghuo Zhu, Weiwei Zhuang, Egemen Tas, Umesh Gupta, Melih Abdulhayoglu. "Combining File Content and File Relations for Cloud Based Malware Detection", Proceedings of ACM International Conference on Knowledge Discovery and Data Mining (ACM SIGKDD), pp. 222~230, 2011. (8% acceptance rate for oral)

  • Yanfang Ye, Tao Li, Yongchen, Qingshan Jiang. "Automatic Malware Categorization Using Cluster Ensemble", Proceedings of ACM International Conference on Knowledge Discovery and Data Mining (ACM SIGKDD), pp. 95~104, 2010. (10.9% acceptance rate for oral)

  • Yanfang Ye, Tao Li, Qingshan Jiang, Zhixue Han, Li Wan. "Intelligent File Scoring System for Malware Detection from the Gray List", Proceedings of ACM International Conference on Knowledge Discovery and Data Mining (ACM SIGKDD), pp. 1385~1394, 2009. (9.8% acceptance rate for oral)

  • Yanfang Ye, Yinming Mei, Rencheng Peng. "MCNS: Intelligent Malware Categorizing and Naming System", The 12th Association of anti Virus Asia Researchers International Conference (AVAR) , pp. 15~25, 2009.

  • Kai Huang, Yanfang Ye, Qingshan Jiang. "ISMCS: An Intelligent Instruction Sequence based Malware Categorization System", International Conference on Anti-counterfeiting, Security, and Identification (ASID), 2009.

  • Youyu Wang, Yanfang Ye, Haishan Chen, Qingshan Jiang. "An Improved Clustering Validity Index for Determining the Number of Malware Clusters", International Conference on Anti-counterfeiting, Security, and Identification (ASID), 2009.

  • Zhixue Han, Yanfang Ye, Shaorong Feng, Qingshan Jiang. "A Parameter-Free Hybrid Clustering algorithm used for Malware Categorization", International Conference on Anti-counterfeiting, Security, and Identification (ASID), 2009.

  • Lifei Chen, Yanfang Ye, Qingshan Jiang. "A New Centroid-Based Classifier for Text Categorization", Advanced Information Networking and Applications Workshops (AINAW), pp. 1217~1222, 2008.

  • Yanfang Ye, Dingding Wang, Tao Li, Dongyi Ye. "IMDS: Intelligent Malware Detection System", Proceedings of ACM International Conference on Knowledge Discovery and Data Mining (ACM SIGKDD), pp. 1043~1047, 2007. (17.9% acceptance rate)

Patents

  • Yanfang Ye, Li Wan, Zhixue Han, Yong Chen. "An intelligent Instruction Frequency based Malware Categorization System and its Methods", Number CN200910040996.8, Awarded 2012.

  • Yanfang Ye, Kai Huang, Fei Liang, Wenxiang Zhu. "An Intelligent Instruction Sequence based Malware Categorization System and its Methods", Number CN200910040997.2, Awarded 2012.

  • Yanfang Ye, Yong Chen, Youyu Wang, Li Wan. "An Improved Clustering Validity Index for Determining the Number of Malware Clusters", Number CN200910040998.7, Awarded 2011.