Selected Publications by Topic
1. AI Robustness: identifying and mitigating vulnerabilities in AI-driven data systems and services.
2. AI Privacy: identifying privacy intrusion attacks in AI-driven data systems and designing privacy-preserving solutions.
3. AI Fairness: eliminating algorithmic bias and improving accountability and transparency of AI-driven data systems.
4. Intelligent Data Service: delivering AI/privacy-preserving/security-aware solutions to intelligent data systems.
5. AI and Cybersecurity Management: Research on implications, management, regulation and policy of AI and cybersecurity in modern information sytems.
Full Publication List
*** with 71 papers (44 in conferences, 23 in journals, 1 in Demo and 3 in Workshops), 1 book chapter, and 3 patents published as of today.
Conference and Workshop Papers
[C44] Xiang Li, Pin-Yu Chen, Wenqi Wei, "Scaling Laws in Model Fine-tuning for Audio DeepFake Detection", International Conference on Machine Learning (ICML). 2026. 6352/23918=26.6%
[C43] Can Jin, Rui Wu, Tong Che, Qixin Zhang, Hongwu Peng, Jiahui Zhao, Zhenting Wang, Wenqi Wei, Ligong Han, Zhao Zhang, Yuan Cao, Ruixiang Tang, and Dimitris N. Metaxas.. "Reasoning over Precedents Alongside Statutes: Case-Augmented Deliberative Alignment for LLM Safety", Annual Meeting of the Association for Computational Linguistics (ACL), San Diego, California, July 2026.
[C42] Xiang Li, Pin-Yu Chen, and Wenqi Wei. "Measuring the Robustness of Audio Deepfake Detection under Real-World Corruption", ACM Conference on Data and Application Security and Privacy (CODASPY), Frankfurt am Main, Germany, June 2026. 30/136=22%
[C41] Zefan Du, Wenrui Zhang, Jake Gesseck, Wenqi Wei, Juntao Chen, Tao Han, Zhiding Liang, and Ying Mao, "Efficient Circuit Management and Scheduling in Multi-Node Quantum Systems with Dynamic Links" IEEE International Conference on Application-specific Systems, Architectures and Processors, 2026
[C40] Zefan Du, Miguel Palma, Zijian Mo, Wenqi Wei, Juntao Chen, Rajkumar Buyya and Ying Mao, "DisMap: Calibration-Aware Distributed Compilation for Multi-Chip Quantum Systems", IEEE International Conference on Quantum Software (QSW). 2026.
[C39] Zhen Wu, Yanni Han, Wen Zhang, and Wenqi Wei. "Leveraging Hyperbolic Geometry for Enhanced Graph-based Anomaly Detection in Microservices", International Conference on Computer Supported Cooperative Work in Design (CSCWD), Fuzhou, China, May 2026.
[C38] Zhen Wu, Yanni Han, and Wenqi Wei. "Harnessing LLMs with Graph Representation Learning for Anomaly Detection in Microservice", IEEE International Conference on Communications (ICC), Glasgow, UK, May 2026.
[C37] Tianyi Yang, Nashrah Haque, Vaishnave Jonnalagadda, Yuya Jeremy Ong, Zhehui Chen, Yanzhao Wu, Lei Yu, Divyesh Jadav, and Wenqi Wei. "Augmenting Question Answering with A Hybrid RAG Approach", IEEE International Conference on Cognitive Machine Intelligence (CogMI), Pittsburgh, PA, Nov 2025.
[C36] Wenqi Wei, Xiang Li, and Hüseyin Tanriverdi. "Software Generation with LLMs: Privacy, Utility, and Cybersecurity Tensions", AIS International Conference on Information Systems (ICIS), Nashville, TN, Dec 2025. Best Student Paper Nomination
[C35] Kerui Wu, Ka-Ho Chow, Wenqi Wei, and Lei Yu. "On the Adversarial Robustness of Graph Neural Networks with Graph Reduction", European Symposium on Research in Computer Security (ESORICS), Toulouse, France, Sept 2025. 100/600=16.7%
[C34] Xiang Li, Bhavani Thuraisingham, and Wenqi Wei. "MUBox: A Critical Evaluation Framework of Deep Machine Unlearning", ACM Symposium on Access Control Models and Technologies (SACMAT), Stony Brook, NY, USA, July 2025.
[C33] Yue Yu, Zhen Wu, Yanni Han, Zhuoqun Li, and Wenqi Wei. "Unlocking Financial Statement Fraud Detection: Tracking Disclosure Changes via Representation Learning", IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Hyderabad, India, April 2025.
[C32] Shoutai Zhu, Ziqiang Yuan, Kaiyuan Wang, Yishu Zhang, and Wenqi Wei. "Enhancing Financial Reasoning in Large Language Models: The Role of Gold Facts", IEEE International Conference on Big Data, Washington DC, Dec 2024.
[C31] Hongpeng Jin, Maryam Akhavan Aghdam, Sai Nath Chowdary Medikonduru, Wenqi Wei, Xuyu Wang, Wenbin Zhang, Yanzhao Wu, "Effective Diversity Optimizations for High Accuracy Deep Ensembles", IEEE International Conference on Cognitive Machine Intelligence (CogMI), Oct 2024.
[C30] Nashrah Haque, Xiang Li, Zhehui Chen, Yanzhao Wu, Lei Yu, Arun Iyengar, Wenqi Wei, "Boosting Imperceptibility of Stable Diffusion-based Adversarial Examples Generation with Momentum”, IEEE International Conference on Trust, Privacy and Security in Intelligent Systems, and Applications (TPS), Oct 2024.
[C29] Shuwen Kan, Zefan Du, Miguel Palma, Samuel A. Stein, Chenxu Liu, Wenqi Wei, Juntao Chen, Ang Li, and Ying Mao. "Scalable Circuit Cutting and Scheduling in a Resource-constrained and Distributed Quantum System." IEEE International Conference on Quantum Computing and Engineering (QCE), Montréal, Québec, Canada, Sep 2024.
[C28] Ka-Ho Chow, Sihao Hu, Tiansheng Huang, Fatih Ilhan, Wenqi Wei, and Ling Liu, "Diversity-driven Privacy Protection Masks Against Unauthorized Face Recognition", Privacy Enhancing Technologies Symposium (PETS), Bristol, UK, July 2024. 148/708=20.9%
[C27] Ka-Ho Chow, Wenqi Wei, Lei Yu, "Imperio: Language-Guided Backdoor Attacks for Arbitrary Model Control", International Joint Conference on Artificial Intelligence (IJCAI), Jeju, August 2024. 791/5651=14.0%
[C26] Sihao Hu, Tiansheng Huang, Ka-Ho Chow, Wenqi Wei, Yanzhao Wu, Ling Liu, "ZipZap: Efficient Training of Language Models for Ethereum Fraud Detection", the ACM Web Conference (theWebConf), Singapore, May 2024. 2575/11566=22.3%
[C25] Fatih Ilhan, Ka-Ho Chow, Sihao Hu, Tiansheng Huang, Selim Tekin, Wenqi Wei, Yanzhao Wu, Myungjin Lee, Ramana Kompella, Hugo Latapie, Gaowen Liu and Ling Liu, "Adaptive Deep Neural Network Inference Optimization with EENet", Winter Conference on Applications of Computer Vision (WACV), Waikoloa, Hawaii, Jan 2024. [pdf]
[C24] Wenqi Wei and Ling Liu, "Gradient Coupling Effect of Poisoning Attacks in Federated Learning", Hawaii International Conference on System Sciences (HICSS), Waikiki, Hawaii, Jan 2024.
[C23] Wenqi Wei, Mu Qiao, and Divyesh Jadav. "GNN-Ensemble: Towards Random Decision Graph Neural Networks", IEEE International Conference on Big Data, Sorrento, Italy, Dec 2023.
[C22] Wenqi Wei, Ka-Ho Chow, Fatih Ilhan, Yanzhao Wu, Ling Liu, "Model Cloaking against Gradient Leakage", IEEE International Conference on Data Mining (ICDM), Shanghai, China, Dec 2023. 200/1003=19.9%
[C21] Yanzhao Wu, Ka-Ho Chow, Wenqi Wei, Ling Liu, "Exploring Model Learning Heterogeneity for Boosting Ensemble Robustness.", IEEE International Conference on Data Mining (ICDM), Shanghai, China, Dec 2023. 200/1003=19.9%
[C20] Hongpeng Jin, Wenqi Wei, Xuyu Wang, Wenbin Zhang and Yanzhao Wu, "Rethinking Learning Rate Tuning in the Era of Large Language Models.", IEEE International Conference on Cognitive Machine Intelligence (CogMI), Atlanta, GA, Nov 2023.
[C19] Xirong Cao, Xiang Li, Divyesh Jadav, Yanzhao Wu, Zhehui Chen, Chen Zeng and Wenqi Wei, "Invisible Watermarking for Audio Generation Diffusion Models", IEEE International Conference on Trust, Privacy and Security in Intelligent Systems, and Applications (TPS), Atlanta, GA, Nov 2023.
[C18] Ka-Ho Chow, Ling Liu, Wenqi Wei, Fatih Ilhan, Yanzhao Wu. "STDLens: Securing Federated Learning Against Model Hijacking Attacks.", IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Vancouver, Canada, June 2023. [pdf] 2359/9155=25.8%
[C17] Gaolei Li, Jun Wu, Wenqi Wei and Yuchen Liu. "Few-Shot Multi-Domain Knowledge Rearming for Context-Aware Defence Against Advanced Persistent Threats.", IEEE International Conference on Smart Applications, Communications and Networking (SmartNets), Istanbul, Turkey, July 2023.
[C16] Wenqi Wei, Mu Qiao, Eric Butler, and Divyesh Jadav. "Graph Representation Learning based Vulnerable Target Identification in Ransomware Attack.", IEEE International Conference on Big Data (Big Data), Osaka, Japan, December 2022. [pdf]
[C15] Stacey Truex, Ling Liu, Emre Gursoy, Wenqi Wei, and Ka-Ho Chow. "The TSC-PFed Architecture for Privacy-Preserving FL", IEEE International Conference on Trust, Privacy and Security in Intelligent Systems, and Applications (TPS), virtual, USA. December 2021. [pdf]
[C14] Yanzhao Wu, Ling Liu, Zhongwei Xie, Ka-Ho Chow, and Wenqi Wei. "Boosting Ensemble Accuracy by Revisiting Ensemble Diversity Metrics", IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Nashville, Tennessee. June 2021. (virtual) [pdf] 1661/7015=23.7%
[C13] Wenqi Wei, Ling Liu, Yanzhao Wu, Gong Su, and Arun Iyengar. "Gradient-Leakage Resilient Federated Learning", IEEE International Conference on Distributed Computing Systems (ICDCS), Washington DC, USA. USA. July 2021. (virtual) [pdf]
[C12] Wenqi Wei, Ling Liu, Margaret Loper, Ka-Ho Chow, Mehmet Emre Gursoy, Stacey Truex, and Yanzhao Wu. "Cross-layer Strategic Ensemble Defense against Adversarial Examples", International Conference on Computing, Networking and Communications (ICNC), Big Island, Hawaii, USA. February 2020. [pdf]
[C11] Wenqi Wei, Ling Liu, Margaret Loper, Ka-Ho Chow, Mehmet Emre Gursoy, Stacey Truex, and Yanzhao Wu. "A Framework for Evaluating Gradient Leakage Attacks in Federated Learning", European Symposium on Research in Computer Security (ESORICS), Guildford, UK. September 2020. (virtual) [pdf] 72/366=19.7%
[C10] Ka-Ho Chow, Ling Liu, Mehmet Emre Gursoy, Stacey Truex, Wenqi Wei, and Yanzhao Wu. "Understanding Object Detection Through An Adversarial Lens", European Symposium on Research in Computer Security (ESORICS), Guildford, UK. September 2020. (virtual) [pdf] 72/366=19.7%
[C9] Wenqi Wei, Ling Liu, Margaret Loper, Ka-Ho Chow, Mehmet Emre Gursoy, Stacey Truex, and Yanzhao Wu, "Adversarial Deception in Deep Learning: Analysis and Mitigation", IEEE International Conference on Trust, Privacy and Security in Intelligent Systems, and Applications (TPS), Atlanta, Georgia, USA. December 2020. (virtual) [pdf][previous arxiv]
[C8] Ka-Ho Chow, Ling Liu, Margaret Loper, Mehmet Emre Gursoy, Stacey Truex, Wenqi Wei and Yanzhao Wu, "Adversarial Objectness Gradient Attacks on Real-time Object Detection Systems", IEEE International Conference on Trust, Privacy and Security in Intelligent Systems, and Applications (TPS), Atlanta, Georgia, USA. December 2020. (virtual) [pdf]
[C7] Yanzhao Wu, Ling Liu, Zhongwei Xie, Juhyun Bae, Ka-Ho Chow, and Wenqi Wei, "Promoting High Diversity Ensemble Learning with EnsembleBench", IEEE International Conference on Cognitive Machine Intelligence (CogMI), Atlanta, Georgia, USA. December 2020. (virtual) [pdf]
[C6] Ka-Ho Chow, Wenqi Wei, Yanzhao Wu, and Ling Liu, “Denoising and Verification Cross-Layer Ensemble Against Black-box Adversarial Attacks”, IEEE International Conference on Big Data (Big Data), Los Angeles, California, USA. December 2019. [pdf]
[C5] Yanzhao Wu, Ling Liu, Juhyun Bae, Ka-Ho Chow, Arun Iyengar, Calton Pu, Wenqi Wei, Lei Yu, and Qi Zhang, “Demystifying Learning Rate Polices for High Accuracy Training of Deep Neural Networks”, IEEE International Conference on Big Data (Big Data), Los Angeles, California, USA. December 2019. [pdf]
[C4] Stacey Truex, Ling Liu, Mehmet Emre Gursoy, Wenqi Wei, and Lei Yu, “Effects of Differential Privacy and Data Skewness on Membership Inference Vulnerability”, IEEE International Conference on Trust, Privacy and Security in Intelligent Systems, and Applications (TPS), Los Angeles, California, USA. December 2019. [pdf]
[C3] Ling Liu, Wenqi Wei, Ka-Ho Chow, Margaret Loper, Mehmet Emre Gursoy, Stacey Truex, and Yanzhao Wu, "Deep Neural Network Ensembles against Deception: Ensemble Diversity, Accuracy and Robustness", IEEE International Conference on Mobile Ad-Hoc and Smart Systems (MASS), Monterey, California, USA. November 2019. [pdf]
[C2] Mehmet Emre Gursoy, Ling Liu, Stacey Truex, Lei Yu, Wenqi Wei. "Utility-aware synthesis of differentially private and attack-resilient location traces", ACM Conference on Computer and Communications Security (CCS), Toronto, Canada. October 2018. [pdf] 134/809=16.6%
[C1] Liu, Ling, Yanzhao Wu, Wenqi Wei, Wenqi Cao, Semih Sahin, and Qi Zhang. "Benchmarking Deep Learning Frameworks: Design Considerations, Metrics and Beyond", IEEE International Conference on Distributed Computing Systems (ICDCS), Vienna, Austria. July 2018. [pdf] 78/378=20.6%
[Workshop3] Khalifa Afane, Wenqi Wei, Ying Mao, Junaid Farooq, and Juntao Chen. "Next-Generation Phishing: How LLM Agents Empower Cyber Attackers." IEEE Conference on Big Data 2024 - Workshop on Cyber Threat Intelligence and Hunting, Washington DC, USA, Dec 2024.
[Workshop2] Rahul Kumar, Gabrielle Ebbrecht, Junaid Farooq, Wenqi Wei, Ying Mao, and Juntao Chen. "SecFedDrive: Securing Federated Learning for Autonomous Driving Against Backdoor Attacks." IEEE Conference on Communications and Network Security (CNS) 2024 - Cyber Resilience Workshop, Taipei, Taiwan, China, Oct 2024.
[Workshop1] Stacey Truex, Ling Liu, Ka-Ho Chow, Mehmet Emre Gursoy, and Wenqi Wei. "LDP-Fed: federated learning with local differential privacy". ACM International Workshop on Edge Systems, Analytics and Networking (EdgeSys), Heraklion, Crete, Greece. April 2020. [pdf] Best Paper Award
[Demo1] Xueqing Zhang, Junkai Zhang, Ka-Ho Chow, Juntao Chen, Ying Mao, Mohamed Rahouti, Xiang Li, Yuchen Liu, and Wenqi Wei, "Visualizing the Shadows: Unveiling Data Poisoning Behaviors in Federated Learning", IEEE International Conference on Distributed Computing Systems (ICDCS), Jersey City, NJ, July 2024. (Demo track)
Journals and Book (chapters)
[J23] Wenqi Wei, Tiansheng Huang, Sihao Hu, Xinxin Fan, Rui Zhang, Jingya Zhou, and Ling Liu. "GradCloak: Gradient Obfuscation for Privacy-Preserving Distributed Learning as a Service", accepted by IEEE Transactions on Services Computing, 2026. (TSC)
[J22] Yue Yu, Zhen Wu, Yanni Han, Ying Ding, and Wenqi Wei, "Improving Financial Statement Fraud Detection: A Large Language Model Processing Approach ", accepted by ACM Transactions on Internet Technology, 2026. (TOIT)
[J21] Wenqi Wei, Balaji Palanisamy, and Jun Wang, "Introduction to the Special Issue on Reliable Infrastructure and Edge Analytics for IoT", accepted by ACM Transactions on Internet Technology, 2026. (TOIT)
[J20] Miguel Palma, Shuwen Kan, Wenqi Wei, Juntao Chen, Kaixun Hua, Sara Mouradian, and Ying Mao, "Hardware-aware and Resource-efficient Circuit Packing and Scheduling on Trapped-Ion Quantum Computers", accepted by IEEE Transactions on Quantum Engineering, 2026.
[J19] Xiang Li, Pin-Yu Chen, and Wenqi Wei, "Where are we in audio deepfake detection? A systematic analysis over generative and detection models", accepted by ACM Transactions on Internet Technology. 2025. (TOIT)
[J18] Ziqiang Yuan, Kaiyuan Wang, Shoutai Zhu, Ye Yuan, Jingya Zhou, Yanlin Zhu, and Wenqi Wei, "FinLLMs: A Framework for Financial Reasoning Dataset Generation with Large Language Models", accepted by IEEE Transactions on Big Data. 2025 (TBD)
[J17] Congcong Zhang, Jingya Zhou, Wenqi Wei, and Yingdan Shi, "Order-Sensitive Competitive Revenue Maximization for Viral Marketing in Social Networks", accepted by Information Sciences. 2025.
[J16] Wenqi Wei and Ling Liu, "Trustworthy Distributed AI Systems: Robustness, Privacy, and Governance", accepted by ACM Computing Surveys (CSUR). 2025.
[J15] Wenqi Wei, Ka-Ho Chow, Yanzhao Wu, and Ling Liu. "Demystifying Data Poisoning Attacks in Distributed Learning as a Service", accepted by IEEE Transactions on Services Computing (TSC), 2024. [pdf]
[J14] Zhenyu Hu, Jingya Zhou, Wenqi Wei, Congcong Zhang and Yingdan Shi. "Predicting Cross-domain Collaboration using Multi-Task Learning", accepted by Expert Systems With Applications, 2024.
[J13] Yanzhao Wu, Ka-Ho Chow, Wenqi Wei, and Ling Liu. "Hierarchical Pruning of Deep Ensembles with Focal Diversity", accepted by ACM Transactions on Intelligent Systems and Technology, 2024. [pdf]
[J12] Wenqi Wei, Ling Liu, Jingya Zhou, Ka-Ho Chow, and Yanzhao Wu. "Securing Distributed SGD against Gradient Leakage Threats", accepted by IEEE Transactions on Parallel and Distributed Systems (TPDS), 2023. [pdf]
[J11] Xigang Sun, Jingya Zhou, Ling Liu, and Wenqi Wei, "Explicit Time Embedding Based Cascade Attention Network for Information Popularity Prediction", accepted by Information Processing and Management (IP&M), 2023. [pdf]
[J10] Huanhuan Xu, Jingya Zhou, Wenqi Wei, and Baolei Cheng, "Multi-user Computation Offloading for Long-term Sequential Tasks in MEC Environments", accepted by Tsinghua Science and Technology. 2023. [pdf]
[J9] Mehmet Emre Gursoy, Ling Liu, Ka-Ho Chow, Stacey Truex, and Wenqi Wei, "An Adversarial Approach to Protocol Analysis and Selection in Local Differential Privacy", accepted by IEEE Transactions on Information Forensics and Security (TIFS), 2022. [pdf]
[J8] Jingya Zhou, Ling Liu, Wenqi Wei, and Jianxi Fan, "Network Representation Learning: From Preprocessing, Feature Extraction to Node Embedding", accepted by ACM Computing Surveys (CSUR). 2022. [pdf]
[J7] Wenqi Wei, and Ling Liu. "Gradient Leakage Attack Resilient Deep Learning", IEEE Transactions on Information Forensics and Security (TIFS), vol. 17, pp. 303-316, 2022. [pdf]
[J6] Yanzhao Wu, Ling Liu, Calton Pu, Wenqi Cao, Semih Sahin, Wenqi Wei, and Qi Zhang, "A Comparative Measurement Study of Deep Learning as a Service Framework", accepted by IEEE Transactions on Services Computing, 2022 (TSC). [pdf]
[J5] Wenqi Wei, and Ling Liu, "Robust Deep Learning Ensemble against Deception", IEEE Transactions on Dependable and Secure Computing (TDSC), 18(4), 1513-1527, 2021. [pdf]
[J4] Wenqi Wei, Qi Zhang, and Ling Liu, "Bitcoin Transaction Forecasting with Deep Network Representation Learning", IEEE Transactions on Emerging Topics in Computing, 9(3), 1359-1371, 2021. [pdf]
[J3] Stacey Truex, Ling Liu, Mehmet Emre Gursoy, Lei Yu, and Wenqi Wei, "Demystifying Membership Inference Attacks in Machine Learning as a Service", accepted by IEEE Transactions on Services Computing, 2021 (TSC). [pdf]
[J2] Mehmet Emre Gursoy, Acar Tamersoy, Stacey Truex, Wenqi Wei, and Ling Liu, "Secure and Utility-Aware Data Collection with Condensed Local Differential Privacy", IEEE Transactions on Dependable and Secure Computing (TDSC), 18(5), 2365-2378, 2021. [pdf]
[J1] Pan Zhou*, Wenqi Wei*, Kaigui Bian, Dapeng Oliver Wu, Yuchong Hu, Qian Wang. "Private and Truthful Aggregative Game for Large-Scale Spectrum Sharing", IEEE Journal on Selected Areas in Communications (JSAC), 35(2), 463-477, 2017. (* equal contribution) [pdf]
[B1] Wenqi Wei, Tiansheng Huang, Zachary Yahn, Anoop Singhal, Margaret Loper, and Ling Liu. "Data Poisoning and Leakage Analysis in Federated Learning", Handbook of Trustworthy Federated Learning, 73-108,. Springer, 2024.
Patents
[3] Mu Qiao, Wenqi Wei, Divyesh Jadav and Roger C Raphael. "Fingerprint Based Graph Adversarial Defense." U.S. Patent Application 18/215,236., 20250005201, 2025.
[2] Mu Qiao, Wenqi Wei, and Divyesh Jadav. "Graph Neural Network Ensemble Learning." U.S. Patent Application 17/562,080, 20230206029A1, 2023.
[1] Mu Qiao, Wenqi Wei, Eric Butler, and Divyesh Jadav. "Machine learning based vulnerable target identification in ransomware attack." U.S. Patent Application 17/113,464, US20220179964A1, 2022.