| 2026 | AAAI | Out-of-Distribution Detection with Positive and Negative Prompt Supervision Using Large Language Models. | Zhixia He, Chen Zhao, Minglai Shao, Xintao Wu, Xujiang Zhao, Dong Li, Qin Tian, Linlin Yu |
| 2026 | AAAI | LLM-Enhanced Energy Contrastive Learning for Out-of-Distribution Detection in Text-Attributed Graphs. | Xiaoxu Ma, Dong Li, Minglai Shao, Xintao Wu, Chen Zhao |
| 2026 | AAAI | AdaptJobRec: Enhancing Conversational Career Recommendation Through an LLM-Powered Agentic System. | Qixin Wang, Dawei Wang, Kun Chen, Yaowei Hu, Puneet Girdhar, Ruoteng Wang, Aadesh Gupta, Chaitanya Devella, Wenlai Guo, Shangwen Huang, Bachir Aoun, Greg Hayworth, Han Li, Xintao Wu |
| 2026 | WWW | Class-Domain Incremental Learning on Graphs via Disentangled Knowledge Distillation. | Qin Tian, Chen Zhao, Xintao Wu, Dong Li, Minglai Shao, Xujiang Zhao, Wenjun Wang |
| 2025 | ACL | Let The Jury Decide: Fair Demonstration Selection for In-Context Learning through Incremental Greedy Evaluation. | Sadaf Md. Halim, Chen Zhao, Xintao Wu, Latifur Khan, Christan Grant, Fariha Ishrat Rahman, Feng Chen |
| 2025 | EMNLP | CausalVLBench: Benchmarking Visual Causal Reasoning in Large Vision-Language Models. | Aneesh Komanduri, Karuna Bhaila, Xintao Wu |
| 2025 | ICDCS | A Client-level Assessment of Collaborative Backdoor Poisoning in Non-IID Federated Learning. | Phung Lai, Guanxiong Liu, NhatHai Phan, Issa Khalil, Abdallah Khreishah, Xintao Wu |
| 2025 | ICDE | Fairness-Aware Active Online Learning with Changing Environments. | Sadaf Md. Halim, Chen Zhao, Xintao Wu, Latifur Khan, Christan Earl Grant, Feng Chen |
| 2025 | KDD | The 4th Workshop on Ethical Artificial Intelligence: Methods and Applications (EAI). | Chen Zhao, Feng Chen, Xintao Wu, Haifeng Chen |
| 2025 | NAACL | Soft Prompting for Unlearning in Large Language Models. | Karuna Bhaila, Minh-Hao Van, Xintao Wu |
| 2024 | AAAI | Robustly Improving Bandit Algorithms with Confounded and Selection Biased Offline Data: A Causal Approach. | Wen Huang, Xintao Wu |
| 2024 | CHASE | On Large Visual Language Models for Medical Imaging Analysis: An Empirical Study. | Minh-Hao Van, Prateek Verma, Xintao Wu |
| 2024 | ECAI | Causal Diffusion Autoencoders: Toward Counterfactual Generation via Diffusion Probabilistic Models. | Aneesh Komanduri, Chen Zhao, Feng Chen, Xintao Wu |
| 2024 | ICDE | Contrastive Learning for Fraud Detection from Noisy Labels. | Vinay M. S., Shuhan Yuan, Xintao Wu |
| 2024 | IJCAI | Learning Causally Disentangled Representations via the Principle of Independent Causal Mechanisms. | Aneesh Komanduri, Yongkai Wu, Feng Chen, Xintao Wu |
| 2024 | IJCAI | Supervised Algorithmic Fairness in Distribution Shifts: A Survey. | Minglai Shao, Dong Li, Chen Zhao, Xintao Wu, Yujie Lin, Qin Tian |
| 2024 | IJCNN | Cascading Failure Prediction in Power Grid Using Node and Edge Attributed Graph Neural Networks. | Karuna Bhaila, Xintao Wu |
| 2024 | IJCNN | Evaluating the Impact of Local Differential Privacy on Utility Loss via Influence Functions. | Alycia N. Carey, Minh-Hao Van, Xintao Wu |
| 2024 | IJCNN | On Prediction Feature Assignment in the Heckman Selection Model. | Huy Mai, Xintao Wu |
| 2024 | KDD | Algorithmic Fairness Generalization under Covariate and Dependence Shifts Simultaneously. | Chen Zhao, Kai Jiang, Xintao Wu, Haoliang Wang, Latifur Khan, Christan Grant, Feng Chen |
| 2024 | KDD | 3rd Workshop on Ethical Artificial Intelligence: Methods and Applications (EAI). | Chen Zhao, Feng Chen, Xintao Wu, Jundong Li, Haifeng Chen |
| 2024 | PAKDD | Robust Influence-Based Training Methods for Noisy Brain MRI. | Minh-Hao Van, Alycia N. Carey, Xintao Wu |
| 2024 | SDM | Local Differential Privacy in Graph Neural Networks: a Reconstruction Approach. | Karuna Bhaila, Wen Huang, Yongkai Wu, Xintao Wu |
| 2023 | ICDM | HINT: Healthy Influential-Noise based Training to Defend against Data Poisoning Attacks. | Minh-Hao Van, Alycia N. Carey, Xintao Wu |
| 2023 | KDD | 2nd Workshop on Ethical Artificial Intelligence: Methods and Applications (EAI). | Chen Zhao, Feng Chen, Xintao Wu, Haifeng Chen, Jiayu Zhou |
| 2023 | KDD | Towards Fair Disentangled Online Learning for Changing Environments. | Chen Zhao, Feng Mi, Xintao Wu, Kai Jiang, Latifur Khan, Christan Grant, Feng Chen |
| 2022 | AAAI | Achieving Counterfactual Fairness for Causal Bandit. | Wen Huang, Lu Zhang, Xintao Wu |
| 2022 | DASFAA | Poisoning Attacks on Fair Machine Learning. | Minh-Hao Van, Wei Du, Xintao Wu, Aidong Lu |
| 2022 | DASFAA | Contrastive Learning for Insider Threat Detection. | M. S. Vinay, Shuhan Yuan, Xintao Wu |
| 2022 | ICDM | Few-shot Anomaly Detection and Classification Through Reinforced Data Selection. | Xiao Han, Depeng Xu, Shuhan Yuan, Xintao Wu |
| 2022 | KDD | 1st ACM SIGKDD Workshop on Ethical Artificial Intelligence: Methods and Applications (EAI-KDD22). | Chen Zhao, Feng Chen, Xintao Wu, Christopher Funk, Anthony Hoogs |
| 2022 | KDD | Adaptive Fairness-Aware Online Meta-Learning for Changing Environments. | Chen Zhao, Feng Mi, Xintao Wu, Kai Jiang, Latifur Khan, Feng Chen |
| 2022 | PAKDD | Coded Hate Speech Detection via Contextual Information. | Depeng Xu, Shuhan Yuan, Yueyang Wang, Angela Uchechukwu Nwude, Lu Zhang, Anna Zajicek, Xintao Wu |
| 2021 | AAAI | A Generative Adversarial Framework for Bounding Confounded Causal Effects. | Yaowei Hu, Yongkai Wu, Lu Zhang, Xintao Wu |
| 2021 | AIED | Classifying Math Knowledge Components via Task-Adaptive Pre-Trained BERT. | Jia Tracy Shen, Michiharu Yamashita, Ethan Prihar, Neil T. Heffernan, Xintao Wu, Sean McGrew, Dongwon Lee |
| 2021 | CIKM | Fair and Robust Classification Under Sample Selection Bias. | Wei Du, Xintao Wu |
| 2021 | ICA3PP | A Modeling and Verification Method of Modbus TCP/IP Protocol. | Jie Wang, Zhichao Chen, Gang Hou, Haoyu Gao, Pengfei Li, Ao Gao, Xintao Wu |
| 2021 | IJCNN | LogBERT: Log Anomaly Detection via BERT. | Haixuan Guo, Shuhan Yuan, Xintao Wu |
| 2021 | KDD | Removing Disparate Impact on Model Accuracy in Differentially Private Stochastic Gradient Descent. | Depeng Xu, Wei Du, Xintao Wu |
| 2021 | PAKDD | Transferable Contextual Bandits with Prior Observations. | Kevin Labille, Wen Huang, Xintao Wu |
| 2021 | WWW | Attent: Active Attributed Network Alignment. | Qinghai Zhou, Liangyue Li, Xintao Wu, Nan Cao, Lei Ying, Hanghang Tong |
| 2021 | SDM | Fairness-aware Agnostic Federated Learning. | Wei Du, Depeng Xu, Xintao Wu, Hanghang Tong |
| 2020 | CIKM | Few-shot Insider Threat Detection. | Shuhan Yuan, Panpan Zheng, Xintao Wu, Hanghang Tong |
| 2020 | DSAA | AdvPL: Adversarial Personalized Learning. | Wei Du, Xintao Wu |
| 2020 | WWW | Fairness through Equality of Effort. | Wen Huang, Yongkai Wu, Lu Zhang, Xintao Wu |
| 2019 | AAAI | One-Class Adversarial Nets for Fraud Detection. | Panpan Zheng, Shuhan Yuan, Xintao Wu, Jun Li, Aidong Lu |
| 2019 | AAAI | SAFE: A Neural Survival Analysis Model for Fraud Early Detection. | Panpan Zheng, Shuhan Yuan, Xintao Wu |
| 2019 | IJCAI | Heterogeneous Gaussian Mechanism: Preserving Differential Privacy in Deep Learning with Provable Robustness. | NhatHai Phan, Minh N. Vu, Yang Liu, Ruoming Jin, Dejing Dou, Xintao Wu, My T. Thai |
| 2019 | IJCAI | Counterfactual Fairness: Unidentification, Bound and Algorithm. | Yongkai Wu, Lu Zhang, Xintao Wu |
| 2019 | IJCAI | Achieving Causal Fairness through Generative Adversarial Networks. | Depeng Xu, Yongkai Wu, Shuhan Yuan, Lu Zhang, Xintao Wu |
| 2019 | PAKDD | Dynamic Anomaly Detection Using Vector Autoregressive Model. | Yuemeng Li, Aidong Lu, Xintao Wu, Shuhan Yuan |
| 2019 | WWW | On Convexity and Bounds of Fairness-aware Classification. | Yongkai Wu, Lu Zhang, Xintao Wu |
| 2019 | WWW | Achieving Differential Privacy and Fairness in Logistic Regression. | Depeng Xu, Shuhan Yuan, Xintao Wu |
| 2018 | IJCAI | Achieving Non-Discrimination in Prediction. | Lu Zhang, Yongkai Wu, Xintao Wu |
| 2018 | KDD | On Discrimination Discovery and Removal in Ranked Data using Causal Graph. | Yongkai Wu, Lu Zhang, Xintao Wu |
| 2018 | PAKDD | DPNE: Differentially Private Network Embedding. | Depeng Xu, Shuhan Yuan, Xintao Wu, NhatHai Phan |
| 2017 | CIKM | Spectrum-based Deep Neural Networks for Fraud Detection. | Shuhan Yuan, Xintao Wu, Jun Li, Aidong Lu |
| 2017 | DSAA | On Spectral Analysis of Directed Signed Graphs. | Yuemeng Li, Xintao Wu, Aidong Lu |
| 2017 | ICDM | Adaptive Laplace Mechanism: Differential Privacy Preservation in Deep Learning. | NhatHai Phan, Xintao Wu, Han Hu, Dejing Dou |
| 2017 | IJCAI | A Causal Framework for Discovering and Removing Direct and Indirect Discrimination. | Lu Zhang, Yongkai Wu, Xintao Wu |
| 2017 | KDD | Achieving Non-Discrimination in Data Release. | Lu Zhang, Yongkai Wu, Xintao Wu |
| 2017 | PAKDD | SNE: Signed Network Embedding. | Shuhan Yuan, Xintao Wu, Yang Xiang |
| 2016 | AAAI | Differential Privacy Preservation for Deep Auto-Encoders: an Application of Human Behavior Prediction. | NhatHai Phan, Yue Wang, Xintao Wu, Dejing Dou |
| 2016 | DSAA | Using Loglinear Model for Discrimination Discovery and Prevention. | Yongkai Wu, Xintao Wu |
| 2016 | EDBT | Using Randomized Response for Differential Privacy Preserving Data Collection. | Yue Wang, Xintao Wu, Donghui Hu |
| 2016 | EDBT | A Two Phase Deep Learning Model for Identifying Discrimination from Tweets. | Shuhan Yuan, Xintao Wu, Yang Xiang |
| 2016 | ICDM | Incorporating Pre-Training in Long Short-Term Memory Networks for Tweets Classification. | Shuhan Yuan, Xintao Wu, Yang Xiang |
| 2016 | IJCAI | Situation Testing-Based Discrimination Discovery: A Causal Inference Approach. | Lu Zhang, Yongkai Wu, Xintao Wu |
| 2015 | ICDM | Block-Organized Topology Visualization for Visual Exploration of Signed Networks. | Xianlin Hu, Leting Wu, Aidong Lu, Xintao Wu |
| 2015 | ICDM | Analysis of Spectral Space Properties of Directed Graphs Using Matrix Perturbation Theory with Application in Graph Partition. | Yuemeng Li, Xintao Wu, Aidong Lu |
| 2015 | IJCAI | Regression Model Fitting under Differential Privacy and Model Inversion Attack. | Yue Wang, Cheng Si, Xintao Wu |
| 2015 | PAKDD | On Burst Detection and Prediction in Retweeting Sequence. | Zhilin Luo, Yue Wang, Xintao Wu, Wandong Cai, Ting Chen |
| 2014 | ICDM | On Spectral Analysis of Signed and Dispute Graphs. | Leting Wu, Xintao Wu, Aidong Lu, Yuemeng Li |
| 2013 | ICSE | Automatic test generation for mutation testing on database applications. | Kai Pan, Xintao Wu, Tao Xie |
| 2013 | PAKDD | Differential Privacy Preserving Spectral Graph Analysis. | Yue Wang, Xintao Wu, Leting Wu |
| 2013 | PAKDD | On Linear Refinement of Differential Privacy-Preserving Query Answering. | Xiaowei Ying, Xintao Wu, Yue Wang |
| 2012 | WISE | Predicting Retweeting Behavior Based on Autoregressive Moving Average Model. | Zhilin Luo, Yue Wang, Xintao Wu |
| 2011 | ICDE | Spectrum based fraud detection in social networks. | Xiaowei Ying, Xintao Wu, Daniel Barbar |
| 2011 | IJCAI | Line Orthogonality in Adjacency Eigenspace with Application to Community Partition. | Leting Wu, Xiaowei Ying, Xintao Wu, Zhi-Hua Zhou |
| 2011 | PAKDD | Spectral Analysis of | Leting Wu, Xiaowei Ying, Xintao Wu, Aidong Lu, Zhi-Hua Zhou |
| 2011 | SIGMOD | Database state generation via dynamic symbolic execution for coverage criteria. | Kai Pan, Xintao Wu, Tao Xie |
| 2010 | CCS | Spectrum based fraud detection in social networks. | Xiaowei Ying, Xintao Wu, Daniel Barbar |
| 2010 | ICDM | On Attribute Disclosure in Randomization Based Privacy Preserving Data Publishing. | Ling Guo, Xiaowei Ying, Xintao Wu |
| 2010 | SDM | Reconstruction from Randomized Graph via Low Rank Approximation. | Leting Wu, Xiaowei Ying, Xintao Wu |
| 2010 | VizSec | Interactive detection of network anomalies via coordinated multiple views. | Lane Harrison, Xianlin Hu, Xiaowei Ying, Aidong Lu, Weichao Wang, Xintao Wu |
| 2009 | KDD | Comparisons of randomization and K-degree anonymization schemes for privacy preserving social network publishing. | Xiaowei Ying, Kai Pan, Xintao Wu, Ling Guo |
| 2009 | PAKDD | On Link Privacy in Randomizing Social Networks. | Xiaowei Ying, Xintao Wu |
| 2009 | SDM | On Randomness Measures for Social Networks. | Xiaowei Ying, Xintao Wu |
| 2009 | SDM | Graph Generation with Prescribed Feature Constraints. | Xiaowei Ying, Xintao Wu |
| 2008 | PAKDD | On Addressing Accuracy Concerns in Privacy Preserving Association Rule Mining. | Ling Guo, Songtao Guo, Xintao Wu |
| 2008 | SDM | Randomizing Social Networks: a Spectrum Preserving Approach. | Xiaowei Ying, Xintao Wu |
| 2007 | PAKDD | Deriving Private Information from Arbitrarily Projected Data. | Songtao Guo, Xintao Wu |
| 2006 | ICDE | Deriving Private Information from Perturbed Data Using IQR Based Approach. | Songtao Guo, Xintao Wu, Yingjiu Li |
| 2006 | ICDM | An Approach to Outsourcing Data Mining Tasks while Protecting Business Intelligence and Customer Privacy. | Ling Qiu, Yingjiu Li, Xintao Wu |
| 2006 | ICISS | Disclosure Risk in Dynamic Two-Dimensional Contingency Tables (Extended Abstract). | Haibing Lu, Yingjiu Li, Xintao Wu |
| 2006 | PSD | Disclosure Analysis for Two-Way Contingency Tables. | Haibing Lu, Yingjiu Li, Xintao Wu |
| 2006 | SAC | On the use of spectral filtering for privacy preserving data mining. | Songtao Guo, Xintao Wu |
| 2006 | SAC | Towards value disclosure analysis in modeling general databases. | Xintao Wu, Songtao Guo, Yingjiu Li |
| 2005 | ICDM | Approximate Inverse Frequent Itemset Mining: Privacy, Complexity, and Approximation. | Yongge Wang, Xintao Wu |
| 2005 | IDEAS | Privacy Aware Data Generation for Testing Database Applications. | Xintao Wu, Chintan Sanghvi, Yongge Wang, Yuliang Zheng |
| 2005 | ISMIS | Statistical Database Modeling for Privacy Preserving Database Generation. | Xintao Wu, Yongge Wang, Yuliang Zheng |
| 2005 | ISMIS | Efficient Causal Interaction Learning with Applications in Microarray. | Yong Ye, Xintao Wu |
| 2005 | SDM | Privacy Aware Market Basket Data Set Generation: A Feasible Approach for Inverse Frequent Set Mining. | Xintao Wu, Ying Wu, Yongge Wang, Yingjiu Li |
| 2004 | ICDE | GenExplore: Interactive Exploration of Gene Interactions from Microarray Data. | Yong Ye, Xintao Wu, Kalpathi R. Subramanian, Liying Zhang |
| 2004 | TrustBus | Privacy Preserving Data Generation for Database Application Performance Testing. | Yongge Wang, Xintao Wu, Yuliang Zheng |
| 2003 | DCC | Compressing High Dimensional Datasets by Fractals. | Xintao Wu, Daniel Barbar |
| 2003 | KDD | Screening and interpreting multi-item associations based on log-linear modeling. | Xintao Wu, Daniel Barbar, Yong Ye |
| 2003 | KDD | Interactive Analysis of Gene Interactions Using Graphical gaussian model. | Xintao Wu, Yong Ye, Kalpathi R. Subramanian |
| 2002 | DaWaK | Modeling and Imputation of Large Incomplete Multidimensional Datasets. | Xintao Wu, Daniel Barbar |
| 2002 | KDD | B-EM: a classifier incorporating bootstrap with EM approach for data mining. | Xintao Wu, Jianping Fan, Kalpathi R. Subramanian |
| 2000 | DaWaK | Supporting Online Queries in ROLAP. | Daniel Barbar, Xintao Wu |
| 1999 | KDD | Using Approximations to Scale Exploratory Data Analysis in Datacubes. | Daniel Barbar, Xintao Wu |