| 2025 | ESORICS | On the Adversarial Robustness of Graph Neural Networks with Graph Reduction. | Kerui Wu, Ka-Ho Chow, Wenqi Wei, Lei Yu |
| 2025 | ICCV | Geminio: Language-Guided Gradient Inversion Attacks in Federated Learning. | Junjie Shan, Ziqi Zhao, Jialin Lu, Rui Zhang, Siu Ming Yiu, Ka-Ho Chow |
| 2025 | ICCV | OCR Hinders RAG: Evaluating the Cascading Impact of OCR on Retrieval-Augmented Generation. | Junyuan Zhang, Qintong Zhang, Bin Wang, Linke Ouyang, Zichen Wen, Ying Li, Ka-Ho Chow, Conghui He, Wentao Zhang |
| 2024 | CVPR | On the Efficiency of Privacy Attacks in Federated Learning. | Nawrin Tabassum, Ka-Ho Chow, Xuyu Wang, Wenbin Zhang, Yanzhao Wu |
| 2024 | ECCV | Personalized Privacy Protection Mask Against Unauthorized Facial Recognition. | Ka-Ho Chow, Sihao Hu, Tiansheng Huang, Ling Liu |
| 2024 | EuroSys | Atlas: Hybrid Cloud Migration Advisor for Interactive Microservices. | Ka-Ho Chow, Umesh Deshpande, Veera Deenadhayalan, Sangeetha Seshadri, Ling Liu |
| 2024 | ICDCS | Demo: Visualizing the Shadows: Unveiling Data Poisoning Behaviors in Federated Learning. | Xueqing Zhang, Junkai Zhang, Ka-Ho Chow, Juntao Chen, Ying Mao, Mohamed Rahouti, Xiang Li, Yuchen Liu, Wenqi Wei |
| 2024 | IJCAI | Imperio: Language-Guided Backdoor Attacks for Arbitrary Model Control. | Ka-Ho Chow, Wenqi Wei, Lei Yu |
| 2024 | WWW | ZipZap: Efficient Training of Language Models for Large-Scale Fraud Detection on Blockchain. | Sihao Hu, Tiansheng Huang, Ka-Ho Chow, Wenqi Wei, Yanzhao Wu, Ling Liu |
| 2024 | WACV | Adaptive Deep Neural Network Inference Optimization with EENet. | Fatih Ilhan, Ka-Ho Chow, Sihao Hu, Tiansheng Huang, Selim F. Tekin, Wenqi Wei, Yanzhao Wu, Myungjin Lee, Ramana Kompella, Hugo Latapie, Gaowen Liu, Ling Liu |
| 2023 | CVPR | STDLens: Model Hijacking-Resilient Federated Learning for Object Detection. | Ka-Ho Chow, Ling Liu, Wenqi Wei, Fatih Ilhan, Yanzhao Wu |
| 2023 | ICDM | Exploring Model Learning Heterogeneity for Boosting Ensemble Robustness. | Yanzhao Wu, Ka-Ho Chow, Wenqi Wei, Ling Liu |
| 2023 | ICDM | Model Cloaking against Gradient Leakage. | Wenqi Wei, Ka-Ho Chow, Fatih Ilhan, Yanzhao Wu, Ling Liu |
| 2023 | WWW | Hierarchical Deep Neural Network Inference for Device-Edge-Cloud Systems. | Fatih Ilhan, Selim Furkan Tekin, Sihao Hu, Tiansheng Huang, Ka-Ho Chow, Ling Liu |
| 2023 | SIGMOD | SCAD: Scalability Advisor for Interactive Microservices on Hybrid Clouds. | Ka-Ho Chow, Umesh Deshpande, Veera Deenadhayalan, Sangeetha Seshadri, Ling Liu |
| 2022 | EuroSys | DeepRest: deep resource estimation for interactive microservices. | Ka-Ho Chow, Umesh Deshpande, Sangeetha Seshadri, Ling Liu |
| 2022 | ICDM | Boosting Object Detection Ensembles with Error Diversity. | Ka-Ho Chow, Ling Liu |
| 2021 | CVPR | Boosting Ensemble Accuracy by Revisiting Ensemble Diversity Metrics. | Yanzhao Wu, Ling Liu, Zhongwei Xie, Ka-Ho Chow, Wenqi Wei |
| 2021 | KDD | Robust Object Detection Fusion Against Deception. | Ka-Ho Chow, Ling Liu |
| 2021 | SIGMOD | SRA: Smart Recovery Advisor for Cyber Attacks. | Ka-Ho Chow, Umesh Deshpande, Sangeetha Seshadri, Ling Liu |
| 2020 | ESORICS | Understanding Object Detection Through an Adversarial Lens. | Ka-Ho Chow, Ling Liu, Mehmet Emre Gursoy, Stacey Truex, Wenqi Wei, Yanzhao Wu |
| 2020 | ESORICS | A Framework for Evaluating Client Privacy Leakages in Federated Learning. | Wenqi Wei, Ling Liu, Margaret Loper, Ka-Ho Chow, Mehmet Emre Gursoy, Stacey Truex, Yanzhao Wu |
| 2020 | EuroSys | LDP-Fed: federated learning with local differential privacy. | Stacey Truex, Ling Liu, Ka-Ho Chow, Mehmet Emre Gursoy, Wenqi Wei |
| 2019 | MASS | Deep Neural Network Ensembles Against Deception: Ensemble Diversity, Accuracy and Robustness. | Ling Liu, Wenqi Wei, Ka-Ho Chow, Margaret Loper, Mehmet Emre Gursoy, Stacey Truex, Yanzhao Wu |