| 2026 | ACL | Conceptual Hierarchies within LLMs. | Tiago Almeida, Zining Zhu, Yue Ning |
| 2025 | AISTATS | DeCaf: A Causal Decoupling Framework for OOD Generalization on Node Classification. | Xiaoxue Han, Huzefa Rangwala, Yue Ning |
| 2025 | CHASE | Task as Context Prompting for Accurate Medical Symptom Coding Using Large Language Models. | Chengyang He, Wenlong Zhang, Violet Xinying Chen, Yue Ning, Ping Wang |
| 2025 | EMNLP | No Black Boxes: Interpretable and Interactable Predictive Healthcare with Knowledge-Enhanced Agentic Causal Discovery. | Xiaoxue Han, Pengfei Hu, Chang Lu, Jun-En Ding, Feng Liu, Yue Ning |
| 2025 | ICDM | Adaptive Graph Learning with Transformer for Multi-Reservoir Inflow Prediction. | Pengfei Hu, Ming Fan, Xiaoxue Han, Chang Lu, Wei Zhang, Hyun Kang, Yue Ning, Dan Lu |
| 2025 | ICDM | Learning for Inflation Forecasting with Dynamic Feature Spaces. | Zakariyya Scavotto, Xiaoxue Han, Yue Ning |
| 2024 | CIKM | RL-ISLAP: A Reinforcement Learning Framework for Industrial-Scale Linear Assignment Problems at Alipay. | Hanjie Li, Yue Ning, Yang Bao, Changsheng Li, Boxiao Chen, Xingyu Lu, Ye Yuan, Guoren Wang |
| 2024 | KDD | Advances in Human Event Modeling: From Graph Neural Networks to Language Models. | Songgaojun Deng, Maarten de Rijke, Yue Ning |
| 2023 | ICDM | Equipping Federated Graph Neural Networks with Structure-aware Group Fairness. | Nan Cui, Xiuling Wang, Wendy Hui Wang, Violet Xinying Chen, Yue Ning |
| 2023 | KDD | Certified Edge Unlearning for Graph Neural Networks. | Kun Wu, Jie Shen, Yue Ning, Ting Wang, Wendy Hui Wang |
| 2022 | AAAI | Context-Aware Health Event Prediction via Transition Functions on Dynamic Disease Graphs. | Chang Lu, Tian Han, Yue Ning |
| 2022 | COMPSAC | A Self-adaptive Indicator Selection Approach for Solving Credit Risk Assessment. | Yongfeng Gu, Yue Ning, Hao Ding, Kecai Gu, Daohong Jian, Zhou Xu, Hua Wu, Jun Zhou |
| 2022 | CVPR | Weakly-supervised Metric Learning with Cross-Module Communications for the Classification of Anterior Chamber Angle Images. | Jingqi Huang, Yue Ning, Dong Nie, Linan Guan, Xiping Jia |
| 2022 | GECCO | Zeroth-order covariance matrix adaptation evolution strategy for single objective bound constrained numerical optimization competition. | Yue Ning, Daohong Jian, Hua Wu, Jun Zhou |
| 2022 | ICDM | Causality Enhanced Societal Event Forecasting With Heterogeneous Graph Learning. | Songgaojun Deng, Huzefa Rangwala, Yue Ning |
| 2022 | ICDM | Text-enhanced Multi-Granularity Temporal Graph Learning for Event Prediction. | Xiaoxue Han, Yue Ning |
| 2022 | ICWSM | Anti-Asian Hate Speech Detection via Data Augmented Semantic Relation Inference. | Jiaxuan Li, Yue Ning |
| 2022 | ICWSM | FairLP: Towards Fair Link Prediction on Social Network Graphs. | Yanying Li, Xiuling Wang, Yue Ning, Hui Wang |
| 2022 | KDD | Robust Event Forecasting with Spatiotemporal Confounder Learning. | Songgaojun Deng, Huzefa Rangwala, Yue Ning |
| 2021 | CIKM | Understanding Event Predictions via Contextualized Multilevel Feature Learning. | Songgaojun Deng, Huzefa Rangwala, Yue Ning |
| 2021 | IJCAI | Collaborative Graph Learning with Auxiliary Text for Temporal Event Prediction in Healthcare. | Chang Lu, Chandan K. Reddy, Prithwish Chakraborty, Samantha Kleinberg, Yue Ning |
| 2021 | PAKDD | Incorporating Relational Knowledge in Explainable Fake News Detection. | Kun Wu, Xu Yuan, Yue Ning |
| 2020 | CIKM | Cola-GNN: Cross-location Attention based Graph Neural Networks for Long-term ILI Prediction. | Songgaojun Deng, Shusen Wang, Huzefa Rangwala, Lijing Wang, Yue Ning |
| 2020 | IJCNN | Federated Multi-task Learning with Hierarchical Attention for Sensor Data Analytics. | Yujing Chen, Yue Ning, Zheng Chai, Huzefa Rangwala |
| 2020 | ICWSM | Empirical Analysis of Multi-Task Learning for Reducing Identity Bias in Toxic Comment Detection. | Ameya Vaidya, Feng Mai, Yue Ning |
| 2020 | KDD | Dynamic Knowledge Graph based Multi-Event Forecasting. | Songgaojun Deng, Huzefa Rangwala, Yue Ning |
| 2020 | WWW | Fairness of Classification Using Users' Social Relationships in Online Peer-To-Peer Lending. | Yanying Li, Yue Ning, Rong Liu, Ying Wu, Wendy Hui Wang |
| 2019 | KDD | Learning Dynamic Context Graphs for Predicting Social Events. | Songgaojun Deng, Huzefa Rangwala, Yue Ning |
| 2019 | KDD | Spatio-temporal Event Forecasting and Precursor Identification. | Yue Ning, Liang Zhao, Feng Chen, Chang-Tien Lu, Huzefa Rangwala |
| 2018 | SDM | STAPLE: Spatio-Temporal Precursor Learning for Event Forecasting. | Yue Ning, Rongrong Tao, Chandan K. Reddy, Huzefa Rangwala, James C. Starz, Naren Ramakrishnan |
| 2017 | AAAI | Determining Relative Airport Threats from News and Social Media. | Rupinder Paul Khandpur, Taoran Ji, Yue Ning, Liang Zhao, Chang-Tien Lu, Erik R. Smith, Christopher Adams, Naren Ramakrishnan |
| 2017 | RecSys | A Gradient-based Adaptive Learning Framework for Efficient Personal Recommendation. | Yue Ning, Yue Shi, Liangjie Hong, Huzefa Rangwala, Naren Ramakrishnan |
| 2016 | AAAI | Topical Analysis of Interactions Between News and Social Media. | Ting Hua, Yue Ning, Feng Chen, Chang-Tien Lu, Naren Ramakrishnan |
| 2016 | CIKM | A Multiple Instance Learning Framework for Identifying Key Sentences and Detecting Events. | Wei Wang, Yue Ning, Huzefa Rangwala, Naren Ramakrishnan |
| 2016 | KDD | Modeling Precursors for Event Forecasting via Nested Multi-Instance Learning. | Yue Ning, Sathappan Muthiah, Huzefa Rangwala, Naren Ramakrishnan |
| 2015 | PIMRC | Energy-efficient BS antenna configuration for downlink distributed MIMO system. | Jiancun Fan, Yue Ning, Jianguo Deng, Ying Zhang, Zhikun Xu |