Rank-Based Multi-task Learning for Fair Regression. - Chen Zhao 010; Feng Chen 001 (ICDM, 2019)

Unfairness Discovery and Prevention For Few-Shot Regression. - Chen Zhao 010; Feng Chen 001 (ICKG, 2020)

Fair Meta-Learning For Few-Shot Classification. - Chen Zhao 010; Changbin Li; Jincheng Li; Feng Chen 001 (ICKG, 2020)

A Primal-Dual Subgradient Approach for Fair Meta Learning. - Chen Zhao 010; Feng Chen 001; Zhuoyi Wang; Latifur Khan (ICDM, 2020)

A Reweighted Meta Learning Framework for Robust Few Shot Learning. - KrishnaTeja Killamsetty; Changbin Li; Chen Zhao 010; Rishabh K. Iyer; Feng Chen 001 (CoRR, 2020)

VSCL: Automating Vulnerability Detection in Smart Contracts with Deep Learning. - Feng Mi; Zhuoyi Wang; Chen Zhao 010; Jinghui Guo; Fawaz Ahmed; Latifur Khan (IEEE ICBC, 2021)

Fairness-Aware Online Meta-learning. - Chen Zhao 010; Feng Chen 001; Bhavani Thuraisingham (KDD, 2021)

CLEAR: Contrastive-Prototype Learning with Drift Estimation for Resource Constrained Stream Mining. - Zhuoyi Wang; Yuqiao Chen; Chen Zhao 010; Yu Lin 002; Xujiang Zhao; Hemeng Tao; Yigong Wang; Latifur Khan (WWW, 2021)

A Nested Bi-level Optimization Framework for Robust Few Shot Learning. - KrishnaTeja Killamsetty; Changbin Li; Chen Zhao 010; Feng Chen 001; Rishabh K. Iyer (AAAI, 2022)

1st ACM SIGKDD Workshop on Ethical Artificial Intelligence: Methods and Applications (EAI-KDD22). - Chen Zhao 010; Feng Chen 001; Xintao Wu; Christopher Funk; Anthony Hoogs (KDD, 2022)

Adaptive Fairness-Aware Online Meta-Learning for Changing Environments. - Chen Zhao 010; Feng Mi; Xintao Wu; Kai Jiang; Latifur Khan; Feng Chen 001 (KDD, 2022)

Layer Adaptive Deep Neural Networks for Out-of-Distribution Detection. - Haoliang Wang; Chen Zhao 010; Xujiang Zhao; Feng Chen 001 (PAKDD (2), 2022)

Contrastive Representation Learning Based on Multiple Node-centered Subgraphs. - Dong Li 034; Wenjun Wang 002; Minglai Shao 001; Chen Zhao 010 (CIKM, 2023)

Adaptation Speed Analysis for Fairness-aware Causal Models. - Yujie Lin; Chen Zhao 010; Minglai Shao 001; Xujiang Zhao; Haifeng Chen (CIKM, 2023)

Open Set Action Recognition via Multi-Label Evidential Learning. - Chen Zhao 010; Dawei Du; Anthony Hoogs; Christopher Funk (CVPR, 2023)

Multi-Label Temporal Evidential Neural Networks for Early Event Detection. - Xujiang Zhao; Xuchao Zhang; Chen Zhao 010; Jin-Hee Cho; Lance M. Kaplan; Dong Hyun Jeong; Audun Jøsang; Haifeng Chen; Feng Chen 001 (ICASSP, 2023)

2nd Workshop on Ethical Artificial Intelligence: Methods and Applications (EAI). - Chen Zhao 010; Feng Chen 001; Xintao Wu; Haifeng Chen; Jiayu Zhou (KDD, 2023)

Towards Fair Disentangled Online Learning for Changing Environments. - Chen Zhao 010; Feng Mi; Xintao Wu; Kai Jiang; Latifur Khan; Christan Grant; Feng Chen 001 (KDD, 2023)

2nd Workshop on Uncertainty Reasoning and Quantification in Decision Making. - Xujiang Zhao; Chen Zhao 010; Feng Chen 001; Jin-Hee Cho; Haifeng Chen (KDD, 2023)

An Automated Vulnerability Detection Framework for Smart Contracts. - Feng Mi; Chen Zhao 010; Zhuoyi Wang; Sadaf Md. Halim; Xiaodi Li 002; Zhouxiang Wu; Latifur Khan; Bhavani Thuraisingham (CoRR, 2023)

Towards Effective Semantic OOD Detection in Unseen Domains: A Domain Generalization Perspective. - Haoliang Wang; Chen Zhao 010; Yunhui Guo; Kai Jiang; Feng Chen 001 (CoRR, 2023)

Pursuing Counterfactual Fairness via Sequential Autoencoder Across Domains. - Yujie Lin; Chen Zhao 010; Minglai Shao 001; Baoluo Meng; Xujiang Zhao; Haifeng Chen (CoRR, 2023)

Fairness-Aware Domain Generalization under Covariate and Dependence Shifts. - Chen Zhao 010; Kai Jiang; Xintao Wu; Haoliang Wang; Latifur Khan; Christan Grant; Feng Chen 001 (CoRR, 2023)

Learning Fair Invariant Representations under Covariate and Correlation Shifts Simultaneously. - Dong Li 034; Chen Zhao 010; Minglai Shao 001; Wenjun Wang 002 (CIKM, 2024)

Causal Diffusion Autoencoders: Toward Counterfactual Generation via Diffusion Probabilistic Models. - Aneesh Komanduri; Chen Zhao 010; Feng Chen 001; Xintao Wu (ECAI, 2024)

Towards Counterfactual Fairness-aware Domain Generalization in Changing Environments. - Yujie Lin; Chen Zhao 010; Minglai Shao 001; Baoluo Meng; Xujiang Zhao; Haifeng Chen (IJCAI, 2024)

Supervised Algorithmic Fairness in Distribution Shifts: A Survey. - Minglai Shao 001; Dong Li 034; Chen Zhao 010; Xintao Wu; Yujie Lin; Qin Tian (IJCAI, 2024)

Algorithmic Fairness Generalization under Covariate and Dependence Shifts Simultaneously. - Chen Zhao 010; Kai Jiang; Xintao Wu; Haoliang Wang; Latifur Khan; Christan Grant; Feng Chen 001 (KDD, 2024)

3rd Workshop on Ethical Artificial Intelligence: Methods and Applications (EAI). - Chen Zhao 010; Feng Chen 001; Xintao Wu; Jundong Li; Haifeng Chen (KDD, 2024)

3rd Workshop on Uncertainty Reasoning and Quantification in Decision Making (UDM). - Xujiang Zhao; Chen Zhao 010; Feng Chen 001; Jin-Hee Cho; Wei Hua; Haifeng Chen (KDD, 2024)

Graphs Generalization under Distribution Shifts. - Qin Tian; Wenjun Wang 002; Chen Zhao 010; Minglai Shao 001; Wang Zhang 001; Dong Li 034 (CoRR, 2024)

Fair Data Generation via Score-based Diffusion Model. - Yujie Lin; Dong Li 034; Chen Zhao 010; Minglai Shao 001 (CoRR, 2024)

FEED: Fairness-Enhanced Meta-Learning for Domain Generalization. - Kai Jiang; Chen Zhao 010; Haoliang Wang; Feng Chen 001 (CoRR, 2024)

MADOD: Generalizing OOD Detection to Unseen Domains via G-Invariance Meta-Learning. - Haoliang Wang; Chen Zhao 010; Feng Chen 001 (CoRR, 2024)

Fair In-Context Learning via Latent Concept Variables. - Karuna Bhaila; Minh-Hao Van; Kennedy Edemacu; Chen Zhao 010; Feng Chen 001; Xintao Wu (CoRR, 2024)

Dynamic Environment Responsive Online Meta-Learning with Fairness Awareness. - Chen Zhao 010; Feng Mi; Xintao Wu; Kai Jiang; Latifur Khan; Feng Chen 001 (ACM Trans. Knowl. Discov. Data, 2024)

Multi-View Unsupervised Column Subset Selection via Combinatorial Search (Student Abstract). - Guihong Wan; Ninghui Hao; Crystal Maung; Haim Schweitzer; Chen Zhao 010; Kun-Hsing Yu; Yevgeniy R. Semenov (AAAI, 2025)

Let The Jury Decide: Fair Demonstration Selection for In-Context Learning through Incremental Greedy Evaluation. - Sadaf Md. Halim; Chen Zhao 010; Xintao Wu; Latifur Khan; Christan Grant; Fariha Ishrat Rahman; Feng Chen 001 (ACL (Findings), 2025)

GDDA: Semantic OOD Detection on Graphs under Covariate Shift via Score-Based Diffusion Models. - Zhixia He; Chen Zhao 010; Minglai Shao 001; Yujie Lin; Dong Li 034; Qin Tian (ICASSP, 2025)

Hypergraph-Based Dynamic Graph Node Classification. - Xiaoxu Ma; Chen Zhao 010; Minglai Shao 001; Yujie Lin (ICASSP, 2025)

MLDGG: Meta-Learning for Domain Generalization on Graphs. - Qin Tian; Chen Zhao 010; Minglai Shao 001; Wenjun Wang 002; Yujie Lin; Dong Li 034 (KDD (1), 2025)

Evidence-Based Out-of-Distribution Detection on Multi-Label Graphs. - Ruomeng Ding; Xujiang Zhao; Chen Zhao 010; Minglai Shao 001; Zhengzhang Chen; Haifeng Chen (SDM, 2025)

Out-of-distribution detection in heterogeneous graphs via energy propagation. - Tao Yin; Chen Zhao 010; Xiaoyan Liu; Minglai Shao 001 (Knowl. Based Syst., 2025)

A Survey on Computational Pathology Foundation Models: Datasets, Adaptation Strategies, and Evaluation Tasks. - Dong Li 034; Guihong Wan; Xintao Wu; Xinyu Wu; Ajit Johnson Nirmal; Christine G. Lian; Peter K. Sorger; Yevgeniy R. Semenov; Chen Zhao 010 (CoRR, 2025)

Multi-Modal Foundation Models for Computational Pathology: A Survey. - Dong Li 034; Guihong Wan; Xintao Wu; Xinyu Wu; Xiaohui Chen; Yi He; Christine G. Lian; Peter K. Sorger; Yevgeniy R. Semenov; Chen Zhao 010 (CoRR, 2025)

A Survey of AI for Materials Science: Foundation Models, LLM Agents, Datasets, and Tools. - Minh-Hao Van; Prateek Verma; Chen Zhao 010; Xintao Wu (CoRR, 2025)