A Transfer Learning Approach for Predictive Modeling of Degenerate Biological Systems. - Na Zou 001; Yun Zhu; Ji Zhu; Mustafa Gökçe Baydogan; Wei Wang 051; Jing Li 016 (Technometrics, 2015)

Global Deep Learning Methods for Multimodality Isointense Infant Brain Image Segmentation. - Zhengyang Wang; Na Zou 001; Dinggang Shen; Shuiwang Ji (CoRR, 2018)

A Data Adaptive Biological Sequence Representation for Supervised Learning. - Hande Cakin; Berk Görgülü; Mustafa Gökçe Baydogan; Na Zou 001; Jing Li 016 (J. Heal. Informatics Res., 2018)

A General Embedding Framework for Heterogeneous Information Learning in Large-Scale Networks. - Xiao Huang 001; Jundong Li; Na Zou 001; Xia Hu 001 (ACM Trans. Knowl. Discov. Data, 2018)

SpecAE: Spectral AutoEncoder for Anomaly Detection in Attributed Networks. - Yuening Li; Xiao Huang 001; Jundong Li; Mengnan Du; Na Zou 001 (CIKM, 2019)

Learning Hierarchical and Shared Features for Improving 3D Neuron Reconstruction. - Hao Yuan 001; Na Zou 001; Shaoting Zhang 001; Hanchuan Peng; Shuiwang Ji (ICDM, 2019)

PyODDS: An End-to-End Outlier Detection System. - Yuening Li; Daochen Zha; Na Zou 001; Xia Hu 001 (CoRR, 2019)

Multi-Channel Graph Convolutional Networks. - Kaixiong Zhou; Qingquan Song; Xiao Huang 001; Daochen Zha; Na Zou 001; Xia Hu 001 (CoRR, 2019)

Non-Local U-Nets for Biomedical Image Segmentation. - Zhengyang Wang; Na Zou 001; Dinggang Shen; Shuiwang Ji (AAAI, 2020)

Multi-Channel Graph Neural Networks. - Kaixiong Zhou; Qingquan Song; Xiao Huang 001; Daochen Zha; Na Zou 001; Xia Hu 001 (IJCAI, 2020)

PyODDS: An End-to-end Outlier Detection System with Automated Machine Learning. - Yuening Li; Daochen Zha; Praveen Kumar Venugopal; Na Zou 001; Xia Hu 001 (WWW (Companion Volume), 2020)

A Unified Taylor Framework for Revisiting Attribution Methods. - Huiqi Deng; Na Zou 001; Mengnan Du; Weifu Chen; Guocan Feng; Xia Hu 001 (AAAI, 2021)

Mutual Information Preserving Back-propagation: Learn to Invert for Faithful Attribution. - Huiqi Deng; Na Zou 001; Weifu Chen; Guocan Feng; Mengnan Du; Xia Hu 001 (KDD, 2021)

Mitigating Gender Bias in Captioning Systems. - Ruixiang Tang; Mengnan Du; Yuening Li; Zirui Liu 001; Na Zou 001; Xia Hu 001 (WWW, 2021)

AutoVideo: An Automated Video Action Recognition System. - Daochen Zha; Zaid Pervaiz Bhat; Yi-Wei Chen; Yicheng Wang; Sirui Ding; Anmoll Kumar Jain; Mohammad Qazim Bhat; Kwei-Herng Lai; Jiaben Chen; Na Zou 001; Xia Hu 001 (CoRR, 2021)

Modeling Techniques for Machine Learning Fairness: A Survey. - Mingyang Wan; Daochen Zha; Ninghao Liu; Na Zou 001 (CoRR, 2021)

Fairness in Deep Learning: A Computational Perspective. - Mengnan Du; Fan Yang 023; Na Zou 001; Xia Hu 001 (IEEE Intell. Syst., 2021)

Fairly Predicting Graft Failure in Liver Transplant for Organ Assigning. - Sirui Ding; Ruixiang Tang; Daochen Zha; Na Zou 001; Kai Zhang 041; Xiaoqian Jiang; Xia Hu 001 (AMIA, 2022)

Towards Automated Imbalanced Learning with Deep Hierarchical Reinforcement Learning. - Daochen Zha; Kwei-Herng Lai; Qiaoyu Tan; Sirui Ding; Na Zou 001; Xia Ben Hu (CIKM, 2022)

AutoVideo: An Automated Video Action Recognition System. - Daochen Zha; Zaid Pervaiz Bhat; Yi-Wei Chen; Yicheng Wang; Sirui Ding; Jiaben Chen; Kwei-Herng Lai; Mohammad Qazim Bhat; Anmoll Kumar Jain; Alfredo Costilla-Reyes; Na Zou 001; Xia Hu 001 (IJCAI, 2022)

FMP: Toward Fair Graph Message Passing against Topology Bias. - Zhimeng Jiang; Xiaotian Han; Chao Fan; Zirui Liu 001; Na Zou 001; Ali Mostafavi; Xia Hu 001 (CoRR, 2022)

Fair Machine Learning in Healthcare: A Review. - Qizhang Feng; Mengnan Du; Na Zou 001; Xia Hu 001 (CoRR, 2022)

Towards Memory Efficient Training via Dual Activation Precision. - Guanchu Wang; Zirui Liu 001; Zhimeng Jiang; Ninghao Liu; Na Zou 001; Xia Ben Hu (CoRR, 2022)

Shortcut Learning of Large Language Models in Natural Language Understanding: A Survey. - Mengnan Du; Fengxiang He; Na Zou 001; Dacheng Tao; Xia Hu 001 (CoRR, 2022)

Mitigating Relational Bias on Knowledge Graphs. - Yu-Neng Chuang; Kwei-Herng Lai; Ruixiang Tang; Mengnan Du; Chia-Yuan Chang 002; Na Zou 001; Xia Hu 001 (CoRR, 2022)

Defense Against Explanation Manipulation. - Ruixiang Tang; Ninghao Liu; Fan Yang 023; Na Zou 001; Xia Hu 001 (Frontiers Big Data, 2022)

PheME: A deep ensemble framework for improving phenotype prediction from multi-modal data. - Shenghan Zhang; Haoxuan Li; Ruixiang Tang; Sirui Ding; Laila Rasmy; Degui Zhi; Na Zou 001; Xia Hu 001 (ICHI, 2023)

Learning Fair Graph Representations via Automated Data Augmentations. - Hongyi Ling; Zhimeng Jiang; Youzhi Luo; Shuiwang Ji; Na Zou 001 (ICLR, 2023)

Graph Mixup with Soft Alignments. - Hongyi Ling; Zhimeng Jiang; Meng Liu 015; Shuiwang Ji; Na Zou 001 (ICML, 2023)

DIVISION: Memory Efficient Training via Dual Activation Precision. - Guanchu Wang; Zirui Liu 001; Zhimeng Jiang; Ninghao Liu; Na Zou 001; Xia Ben Hu (ICML, 2023)

Data-centric AI: Techniques and Future Perspectives. - Daochen Zha; Kwei-Herng Lai; Fan Yang 023; Na Zou 001; Huiji Gao; Xia Hu 001 (KDD, 2023)

Fair Graph Distillation. - Qizhang Feng; Zhimeng Stephen Jiang; Ruiquan Li; Yicheng Wang; Na Zou 001; Jiang Bian 001; Xia Hu 001 (NeurIPS, 2023)

Chasing Fairness Under Distribution Shift: A Model Weight Perturbation Approach. - Zhimeng Stephen Jiang; Xiaotian Han; Hongye Jin; Guanchu Wang; Rui Chen 012; Na Zou 001; Xia Hu 001 (NeurIPS, 2023)

Mitigating Algorithmic Bias with Limited Annotations. - Guanchu Wang; Mengnan Du; Ninghao Liu; Na Zou 001; Xia Ben Hu (ECML/PKDD (2), 2023)

RELIANT: Fair Knowledge Distillation for Graph Neural Networks. - Yushun Dong; Binchi Zhang; Yiling Yuan; Na Zou 001; Qi Wang; Jundong Li (SDM, 2023)

Retiring $Δ$DP: New Distribution-Level Metrics for Demographic Parity. - Xiaotian Han; Zhimeng Jiang; Hongye Jin; Zirui Liu 001; Na Zou 001; Qifan Wang 001; Xia Hu 001 (CoRR, 2023)

Understanding and Unifying Fourteen Attribution Methods with Taylor Interactions. - Huiqi Deng; Na Zou 001; Mengnan Du; Weifu Chen; Guocan Feng; Ziwei Yang; Zheyang Li; Quanshi Zhang (CoRR, 2023)

Weight Perturbation Can Help Fairness under Distribution Shift. - Zhimeng Jiang; Xiaotian Han; Hongye Jin; Guanchu Wang; Na Zou 001; Xia Ben Hu (CoRR, 2023)

Towards Fair Patient-Trial Matching via Patient-Criterion Level Fairness Constraint. - Chia-Yuan Chang 002; Jiayi Yuan 001; Sirui Ding; Qiaoyu Tan; Kai Zhang 041; Xiaoqian Jiang; Xia Hu 001; Na Zou 001 (CoRR, 2023)

Multi-Task Learning for Post-transplant Cause of Death Analysis: A Case Study on Liver Transplant. - Sirui Ding; Qiaoyu Tan; Chia-Yuan Chang 002; Na Zou 001; Kai Zhang 041; Nathan R. Hoot; Xiaoqian Jiang; Xia Hu 001 (CoRR, 2023)

Towards Assumption-free Bias Mitigation. - Chia-Yuan Chang 002; Yu-Neng Chuang; Kwei-Herng Lai; Xiaotian Han; Xia Hu 001; Na Zou 001 (CoRR, 2023)

Beyond Fairness: Age-Harmless Parkinson's Detection via Voice. - Yicheng Wang; Xiaotian Han; Leisheng Yu; Na Zou 001 (CoRR, 2023)

CODA: Temporal Domain Generalization via Concept Drift Simulator. - Chia-Yuan Chang 002; Yu-Neng Chuang; Zhimeng Jiang; Kwei-Herng Lai; Anxiao Jiang; Na Zou 001 (CoRR, 2023)

Multi-task learning with dynamic re-weighting to achieve fairness in healthcare predictive modeling. - Can Li; Sirui Ding; Na Zou 001; Xia Hu 001; Xiaoqian Jiang; Kai Zhang 041 (J. Biomed. Informatics, 2023)

Retiring ΔDP: New Distribution-Level Metrics for Demographic Parity. - Xiaotian Han; Zhimeng Jiang; Hongye Jin; Zirui Liu 001; Na Zou 001; Qifan Wang 001; Xia Hu 001 (Trans. Mach. Learn. Res., 2023)

In-Processing Modeling Techniques for Machine Learning Fairness: A Survey. - Mingyang Wan; Daochen Zha; Ninghao Liu; Na Zou 001 (ACM Trans. Knowl. Discov. Data, 2023)

Marginal Nodes Matter: Towards Structure Fairness in Graphs. - Xiaotian Han; Kaixiong Zhou; Ting-Hsiang Wang; Jundong Li; Fei Wang 062; Na Zou 001 (SIGKDD Explor., 2023)

Chasing Fairness in Graphs: A GNN Architecture Perspective. - Zhimeng Jiang; Xiaotian Han; Chao Fan; Zirui Liu 001; Na Zou 001; Ali Mostafavi; Xia Hu 001 (AAAI, 2024)

FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods. - Xiaotian Han; Jianfeng Chi; Yu Chen 022; Qifan Wang 001; Han Zhao 002; Na Zou 001; Xia Hu 001 (ICLR, 2024)

IDEA: A Flexible Framework of Certified Unlearning for Graph Neural Networks. - Yushun Dong; Binchi Zhang; Zhenyu Lei 004; Na Zou 001; Jundong Li (KDD, 2024)

Gradient Rewiring for Editable Graph Neural Network Training. - Zhimeng Jiang; Zirui Liu 001; Xiaotian Han; Qizhang Feng; Hongye Jin; Qiaoyu Tan; Kaixiong Zhou; Na Zou 001; Xia Ben Hu (NeurIPS, 2024)

Identify and mitigate bias in electronic phenotyping: A comprehensive study from computational perspective. - Sirui Ding; Shenghan Zhang; Xia Hu 001; Na Zou 001 (J. Biomed. Informatics, 2024)

Unifying Fourteen Post-Hoc Attribution Methods With Taylor Interactions. - Huiqi Deng; Na Zou 001; Mengnan Du; Weifu Chen; Guocan Feng; Ziwei Yang; Zheyang Li; Quanshi Zhang (IEEE Trans. Pattern Anal. Mach. Intell., 2024)

Shortcut Learning of Large Language Models in Natural Language Understanding. - Mengnan Du; Fengxiang He; Na Zou 001; Dacheng Tao; Xia Hu 001 (Commun. ACM, 2024)

MAIN-RAG: Multi-Agent Filtering Retrieval-Augmented Generation. - Chia-Yuan Chang 002; Zhimeng Jiang; Vineeth Rakesh; Menghai Pan; Chin-Chia Michael Yeh; Guanchu Wang; Mingzhi Hu; Zhichao Xu; Yan Zheng 001; Mahashweta Das; Na Zou 001 (ACL (1), 2025)

Quantized Can Still Be Calibrated: A Unified Framework to Calibration in Quantized Large Language Models. - Mingyu Zhong; Guanchu Wang; Yu-Neng Chuang; Na Zou 001 (ACL (1), 2025)

Discover important donor-recipient risk factors and interactions in heart transplant primary graft dysfunction with machine learning. - Sirui Ding; Yafen Liang; Chia-Yuan Chang 002; Cheryl Brown; Xiaoqian Jiang; Xia Ben Hu; Na Zou 001 (J. Am. Medical Informatics Assoc., 2025)

Counterfactual Fairness on Graphs: Augmentations, Hidden Confounders, and Identifiability. - Hongyi Ling; Zhimeng Jiang; Na Zou 001; Shuiwang Ji (Trans. Mach. Learn. Res., 2025)

Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models. - Yang Sui; Yu-Neng Chuang; Guanchu Wang; Jiamu Zhang; Tianyi Zhang; Jiayi Yuan 001; Hongyi Liu; Andrew Wen; Shaochen Zhong; Na Zou 001; Hanjie Chen; Xia Hu 001 (Trans. Mach. Learn. Res., 2025)

Fair-RGNN: Mitigating Relational Bias on Knowledge Graphs. - Yu-Neng Chuang; Kwei-Herng Lai; Ruixiang Tang; Mengnan Du; Chia-Yuan Chang 002; Na Zou 001; Xia Hu 001 (ACM Trans. Knowl. Discov. Data, 2025)

Fair Machine Learning in Healthcare: A Survey. - Qizhang Feng; Mengnan Du; Na Zou 001; Xia Ben Hu (IEEE Trans. Artif. Intell., 2025)

Rethinking the Understanding Ability across LLMs through Mutual Information. - Shaojie Wang; Sirui Ding; Na Zou 001 (CoRR, 2025)