| 2026 | AAAI | Taming Cascaded Mixture-of-Experts for Modality-missing Multi-modal Salient Object Detection. | Kunpeng Wang, Feifan Sun, Keke Chen |
| 2025 | AAAI | Alignment-Free RGB-T Salient Object Detection: A Large-Scale Dataset and Progressive Correlation Network. | Kunpeng Wang, Keke Chen, Chenglong Li, Zhengzheng Tu, Bin Luo |
| 2025 | ICDM | Auditing Approximate Machine Unlearning for Differentially Private Models. | Yuechun Gu, Jiajie He, Keke Chen |
| 2025 | KDD | Adaptive Domain Inference Attack with Concept Hierarchy. | Yuechun Gu, Jiajie He, Keke Chen |
| 2025 | RecSys | RecPS: Privacy Risk Scoring for Recommender Systems. | Jiajie He, Yuechun Gu, Keke Chen |
| 2024 | CCS | Demo: FT-PrivacyScore: Personalized Privacy Scoring Service for Machine Learning Participation. | Yuechun Gu, Jiajie He, Keke Chen |
| 2023 | AAAI | GAN-Based Domain Inference Attack. | Yuechun Gu, Keke Chen |
| 2023 | CCS | Demo: Image Disguising for Scalable GPU-accelerated Confidential Deep Learning. | Yuechun Gu, Sagar Sharma, Keke Chen |
| 2023 | ICDCS | Demo: SGX-MR-Prot: Efficient and Developer-Friendly Access-Pattern Protection in Trusted Execution Environments. | A. K. M. Mubashwir Alam, Justin Boyce, Keke Chen |
| 2023 | MICCAI | Thinking Like Sonographers: A Deep CNN Model for Diagnosing Gout from Musculoskeletal Ultrasound. | Zhi Cao, Weijing Zhang, Keke Chen, Di Zhao, Daoqiang Zhang, Hongen Liao, Fang Chen |
| 2021 | ICANN | Weakly Supervised Semantic Segmentation with Patch-Based Metric Learning Enhancement. | Patrick P. K. Chan, Keke Chen, Linyi Xu, Xiaoman Hu, Daniel S. Yeung |
| 2021 | IJCNN | Class-Specific Affinity based Weakly Supervised Semantic Segmentation with Neutral Region Exploration. | Keke Chen, Patrick P. K. Chan, Tianyi Xiang, Natasha Kees, Daniel S. Yeung |
| 2019 | ESORICS | Confidential Boosting with Random Linear Classifiers for Outsourced User-Generated Data. | Sagar Sharma, Keke Chen |
| 2019 | ICWSM | Who Should Be the Captain This Week?Leveraging Inferred Diversity-Enhanced Crowd Wisdom for a Fantasy Premier League Captain Prediction. | Shreyansh P. Bhatt, Keke Chen, Valerie L. Shalin, Amit P. Sheth, Brandon S. Minnery |
| 2019 | WSDM | Knowledge Graph Enhanced Community Detection and Characterization. | Shreyansh P. Bhatt, Swati Padhee, Amit P. Sheth, Keke Chen, Valerie L. Shalin, Derek Doran, Brandon S. Minnery |
| 2018 | CCS | Image Disguising for Privacy-preserving Deep Learning. | Sagar Sharma, Keke Chen |
| 2018 | CCS | Privacy-Preserving Boosting with Random Linear Classifiers. | Sagar Sharma, Keke Chen |
| 2018 | ICMLC | Unsupervised Shilling Attack Detection Model Based on Rated Item Correlation Analysis. | Keke Chen, Patrick P. K. Chan, Daniel S. Yeung |
| 2018 | SMC | Shilling Attack Detection Using Rated Item Correlation for Collaborative Filtering. | Keke Chen, Patrick P. K. Chan, Daniel S. Yeung |
| 2017 | ICDCS | PrivateGraph: A Cloud-Centric System for Spectral Analysis of Large Encrypted Graphs. | Sagar Sharma, Keke Chen |
| 2016 | CCS | Privacy-Preserving Spectral Analysis of Large Graphs in Public Clouds. | Sagar Sharma, James Powers, Keke Chen |
| 2016 | ICICS | DynaEgo: Privacy-Preserving Collaborative Filtering Recommender System Based on Social-Aware Differential Privacy. | Shen Yan, Shiran Pan, Wen Tao Zhu, Keke Chen |
| 2016 | WWW | Tweet Properly: Analyzing Deleted Tweets to Understand and Identify Regrettable Ones. | Lu Zhou, Wenbo Wang, Keke Chen |
| 2015 | WWW | Identifying Regrettable Messages from Tweets. | Lu Zhou, Wenbo Wang, Keke Chen |
| 2013 | ICDM | PerturBoost: Practical Confidential Classifier Learning in the Cloud. | Keke Chen, Shumin Guo |
| 2012 | CCS | Privacy preserving boosting in the cloud with secure half-space queries. | Shumin Guo, Keke Chen |
| 2011 | SSDBM | CloudVista: Visual Cluster Exploration for Extreme Scale Data in the Cloud. | Keke Chen, Huiqi Xu, Fengguang Tian, Shumin Guo |
| 2010 | COLING | Cross-Market Model Adaptation with Pairwise Preference Data for Web Search Ranking. | Jing Bai, Fernando Diaz, Yi Chang, Zhaohui Zheng, Keke Chen |
| 2009 | CIKM | On domain similarity and effectiveness of adapting-to-rank. | Keke Chen, Jing Bai, Srihari Reddy, Belle L. Tseng |
| 2008 | CIKM | Trada: tree based ranking function adaptation. | Keke Chen, Rongqing Lu, C. K. Wong, Gordon Sun, Larry P. Heck, Belle L. Tseng |
| 2008 | ICDE | Adapting ranking functions to user preference. | Keke Chen, Ya Zhang, Zhaohui Zheng, Hongyuan Zha, Gordon Sun |
| 2007 | PODC | Space adaptation: privacy-preserving multiparty collaborative mining with geometric perturbation. | Keke Chen, Ling Liu |
| 2007 | SIGIR | A regression framework for learning ranking functions using relative relevance judgments. | Zhaohui Zheng, Keke Chen, Gordon Sun, Hongyuan Zha |
| 2007 | SDM | Towards Attack-Resilient Geometric Data Perturbation. | Keke Chen, Gordon Sun, Ling Liu |
| 2006 | CIKM | Efficiently clustering transactional data with weighted coverage density. | Hua Yan, Keke Chen, Ling Liu |
| 2006 | SDM | Detecting the Change of Clustering Structure in Categorical Data Streams. | Keke Chen, Ling Liu |
| 2005 | ICDM | Privacy Preserving Data Classification with Rotation Perturbation. | Keke Chen, Ling Liu |
| 2005 | SSDBM | The "Best K" for Entropy-based Categorical Data Clustering. | Keke Chen, Ling Liu |
| 2004 | CIKM | ClusterMap: labeling clusters in large datasets via visualization. | Keke Chen, Ling Liu |
| 2003 | ICDM | Validating and Refining Clusters via Visual Rendering. | Keke Chen, Ling Liu |
| 2003 | SAC | Cluster Rendering of Skewed Datasets via Visualization. | Keke Chen, Ling Liu |
| 2003 | SSDBM | A Visual Framework Invites Human into the Clustering Process. | Keke Chen, Ling Liu |