| 2025 | CHI | Diagnosing and Prioritizing Issues in Automated Order-Taking Systems: A Machine-Assisted Error Discovery Approach. | Maeda F. Hanafi, Frederick Reiss, Yannis Katsis, Robert Moore, Mohammad Hassan Falakmasir, Pauline Wang, David Wood, Changchang Liu |
| 2025 | ISSRE | AetherLog: Log-based Root Cause Analysis by Integrating Large Language Models with Knowledge Graphs. | Tianyu Cui, Ruowei Fu, Changchang Liu, Yuhe Ji, Wenwei Gu, Shenglin Zhang, Yongqian Sun, Dan Pei |
| 2024 | CHI | Machine-Assisted Error Discovery in Conversational AI Systems. | Maeda F. Hanafi, Frederick Reiss, Yannis Katsis, Robert Moore, David Wood, Mohammad Hassan Falakmasir, Changchang Liu |
| 2023 | ACL | Federated Learning for Semantic Parsing: Task Formulation, Evaluation Setup, New Algorithms. | Tianshu Zhang, Changchang Liu, Wei-Han Lee, Yu Su, Huan Sun |
| 2021 | CCS | AHEAD: Adaptive Hierarchical Decomposition for Range Query under Local Differential Privacy. | Linkang Du, Zhikun Zhang, Shaojie Bai, Changchang Liu, Shouling Ji, Peng Cheng, Jiming Chen |
| 2020 | CCS | Text Captcha Is Dead? A Large Scale Deployment and Empirical Study. | Chenghui Shi, Shouling Ji, Qianjun Liu, Changchang Liu, Yuefeng Chen, Yuan He, Zhe Liu, Raheem Beyah, Ting Wang |
| 2020 | DSN | Neuraltran: Optimal Data Transformation for Privacy-Preserving Machine Learning by Leveraging Neural Networks. | Changchang Liu, Wei-Han Lee, Seraphin B. Calo |
| 2020 | ICDCS | Communication-efficient k-Means for Edge-based Machine Learning. | Hanlin Lu, Ting He, Shiqiang Wang, Changchang Liu, Mehrdad Mahdavi, Vijaykrishnan Narayanan, Kevin S. Chan, Stephen Pasteris |
| 2020 | ICPR | NeuralFP: Out-of-distribution Detection using Fingerprints of Neural Networks. | Wei-Han Lee, Steve Millman, Nirmit Desai, Mudhakar Srivatsa, Changchang Liu |
| 2020 | ICPR | Overcoming Noisy and Irrelevant Data in Federated Learning. | Tiffany Tuor, Shiqiang Wang, Bong Jun Ko, Changchang Liu, Kin K. Leung |
| 2020 | Networking | Joint Coreset Construction and Quantization for Distributed Machine Learning. | Hanlin Lu, Changchang Liu, Shiqiang Wang, Ting He, Vijaykrishnan Narayanan, Kevin S. Chan, Stephen Pasteris |
| 2019 | ICIP | Exact Incremental and Decremental Learning for LS-SVM. | Wei-Han Lee, Bong Jun Ko, Shiqiang Wang, Changchang Liu, Kin K. Leung |
| 2018 | ESORICS | Secure Model Fusion for Distributed Learning Using Partial Homomorphic Encryption. | Changchang Liu, Supriyo Chakraborty, Dinesh C. Verma |
| 2017 | ICISSP | Quantification of De-anonymization Risks in Social Networks. | Wei-Han Lee, Changchang Liu, Shouling Ji, Prateek Mittal, Ruby B. Lee |
| 2017 | ICISSP | How to Quantify Graph De-anonymization Risks. | Wei-Han Lee, Changchang Liu, Shouling Ji, Prateek Mittal, Ruby B. Lee |
| 2016 | NDSS | LinkMirage: Enabling Privacy-preserving Analytics on Social Relationships. | Changchang Liu, Prateek Mittal |
| 2016 | NDSS | Dependence Makes You Vulnberable: Differential Privacy Under Dependent Tuples. | Changchang Liu, Supriyo Chakraborty, Prateek Mittal |
| 2015 | ACSAC | PARS: A Uniform and Open-source Password Analysis and Research System. | Shouling Ji, Shukun Yang, Ting Wang, Changchang Liu, Wei-Han Lee, Raheem A. Beyah |
| 2015 | CCS | Exploiting Temporal Dynamics in Sybil Defenses. | Changchang Liu, Peng Gao, Matthew K. Wright, Prateek Mittal |
| 2013 | ACSSC | Analyzing the FD-MIMO sparse imaging under carrier frequency offsets from the perspective of point spread function. | Li Ding, Changchang Liu, Weidong Chen |
| 2012 | ACSSC | Sparse frequency diverse MIMO radar imaging. | Changchang Liu, Weidong Chen |
| 2012 | ACSSC | A correction and generalization to the sparse learning via iterative minimization method for target off the grid in MIMO radar imaging. | Changchang Liu, Li Ding, Weidong Chen |
| 2012 | ICASSP | Sparse self-calibration by map method for MIMO radar imaging. | Changchang Liu, Jin Yan, Weidong Chen |