| 2026 | AAAI | Debiased Cognitive Diagnosis: A Contrastive Counterfactual Modeling Method via Variational Autoencoder. | Shangshang Yang, Xuewen Duan, Xiaoshan Yu, Ziwen Wang, Haiping Ma, Xingyi Zhang |
| 2026 | AAAI | PEOAT: Personalization-Guided Evolutionary Question Assembly for One-Shot Adaptive Testing. | Xiaoshan Yu, Ziwei Huang, Shangshang Yang, Ziwen Wang, Haiping Ma, Xingyi Zhang |
| 2026 | KDD | Breaking Robustness Barriers in Cognitive Diagnosis: A One-Shot Neural Architecture Search Perspective. | Ziwen Wang, Shangshang Yang, Xiaoshan Yu, Haiping Ma, Xingyi Zhang |
| 2025 | AAAI | AD4CD: Causal-Guided Anomaly Detection for Enhancing Cognitive Diagnosis. | Haiping Ma, Yue Yao, Changqian Wang, Siyu Song, Yong Yang |
| 2025 | AAAI | Explicit and Implicit Examinee-Question Relation Exploiting for Efficient Computerized Adaptive Testing. | Changqian Wang, Shangshang Yang, Siyu Song, Ziwen Wang, Haiping Ma, Xingyi Zhang, Bo Jin |
| 2025 | IJCAI | Endowing Interpretability for Neural Cognitive Diagnosis by Efficient Kolmogorov-Arnold Networks. | Shangshang Yang, Linrui Qin, Xiaoshan Yu, Ziwen Wang, Xueming Yan, Haiping Ma, Ye Tian |
| 2025 | KDD | Rethinking Learner Modeling: A Feedback-Centric Cognitive Disentanglement Perspective. | Xiaoshan Yu, Shangshang Yang, Jian Li, Ziwen Wang, Chuan Qin, Haiping Ma, Xingyi Zhang |
| 2025 | KDD | Diffusion-Inspired Cold Start with Sufficient Prior in Computerized Adaptive Testing. | Haiping Ma, Aoqing Xia, Changqian Wang, Hai Wang, Xingyi Zhang |
| 2025 | KDD | Learning Patterns-Guided Data Generation for Knowledge Tracing. | Haiping Ma, Yi Yin, Ziwen Wang, Changqian Wang, Xiaoshan Yu, Shangshang Yang, Xingyi Zhang |
| 2025 | WWW | Spatial-Temporal Analysis of Collective Emotional Resonance in China During Global Health Crisis. | Limiao Zhang, Xinyang Qi, Haiping Ma, Jie Gao, Xingyi Zhang, Yanqing Hu, Yaochu Jin |
| 2025 | SIGIR | LIGHT: Enhancing Learning Path Recommendation via Knowledge Topology-Aware Sequence Optimization. | Xiaoshan Yu, Shangshang Yang, Ziwen Wang, Siyu Song, Haiping Ma, Zhiguang Cao, Xingyi Zhang |
| 2025 | SIGIR | Reconciling Efficiency and Effectiveness of Exercise Retreival: An Uncertainty Reduction Hashing Approach for Computerized Adaptive Testing. | Haiping Ma, Weiyuan Zhou, Xiaoshan Yu, Changqian Wang, Shangshang Yang, Limiao Zhang, Xingyi Zhang |
| 2024 | AAAI | Enhancing Cognitive Diagnosis Using Un-interacted Exercises: A Collaboration-Aware Mixed Sampling Approach. | Haiping Ma, Changqian Wang, Hengshu Zhu, Shangshang Yang, Xiaoming Zhang, Xingyi Zhang |
| 2024 | ICDM | DISCO: A Hierarchical Disentangled Cognitive Diagnosis Framework for Interpretable Job Recommendation. | Xiaoshan Yu, Chuan Qin, Qi Zhang, Chen Zhu, Haiping Ma, Xingyi Zhang, Hengshu Zhu |
| 2024 | IJCAI | DGCD: An Adaptive Denoising GNN for Group-level Cognitive Diagnosis. | Haiping Ma, Siyu Song, Chuan Qin, Xiaoshan Yu, Limiao Zhang, Xingyi Zhang, Hengshu Zhu |
| 2024 | KDD | RIGL: A Unified Reciprocal Approach for Tracing the Independent and Group Learning Processes. | Xiaoshan Yu, Chuan Qin, Dazhong Shen, Shangshang Yang, Haiping Ma, Hengshu Zhu, Xingyi Zhang |
| 2024 | WWW | HD-KT: Advancing Robust Knowledge Tracing via Anomalous Learning Interaction Detection. | Haiping Ma, Yong Yang, Chuan Qin, Xiaoshan Yu, Shangshang Yang, Xingyi Zhang, Hengshu Zhu |
| 2023 | CIKM | Homogeneous Cohort-Aware Group Cognitive Diagnosis: A Multi-grained Modeling Perspective. | Shuhuan Liu, Xiaoshan Yu, Haiping Ma, Ziwen Wang, Chuan Qin, Xingyi Zhang |
| 2023 | ICDM | ReliCD: A Reliable Cognitive Diagnosis Framework with Confidence Awareness. | Yunfei Zhang, Chuan Qin, Dazhong Shen, Haiping Ma, Le Zhang, Xingyi Zhang, Hengshu Zhu |
| 2022 | AAAI | Fully Adaptive Framework: Neural Computerized Adaptive Testing for Online Education. | Yan Zhuang, Qi Liu, Zhenya Huang, Zhi Li, Shuanghong Shen, Haiping Ma |
| 2022 | CIKM | Knowledge-Sensed Cognitive Diagnosis for Intelligent Education Platforms. | Haiping Ma, Manwei Li, Le Wu, Haifeng Zhang, Yunbo Cao, Xingyi Zhang, Xuemin Zhao |
| 2022 | CIKM | A Prerequisite Attention Model for Knowledge Proficiency Diagnosis of Students. | Haiping Ma, Jinwei Zhu, Shangshang Yang, Qi Liu, Haifeng Zhang, Xingyi Zhang, Yunbo Cao, Xuemin Zhao |
| 2022 | IJCAI | Reconciling Cognitive Modeling with Knowledge Forgetting: A Continuous Time-aware Neural Network Approach. | Haiping Ma, Jingyuan Wang, Hengshu Zhu, Xin Xia, Haifeng Zhang, Xingyi Zhang, Lei Zhang |
| 2021 | SIGIR | Privileged Graph Distillation for Cold Start Recommendation. | Shuai Wang, Kun Zhang, Le Wu, Haiping Ma, Richang Hong, Meng Wang |
| 2021 | WSDM | Federated Deep Knowledge Tracing. | Jinze Wu, Zhenya Huang, Qi Liu, Defu Lian, Hao Wang, Enhong Chen, Haiping Ma, Shijin Wang |
| 2020 | CEC | An Overlapping Community Detection Based Multi-Objective Evolutionary Algorithm for Diversified Social Influence Maximization. | Lei Zhang, Fengiiao Sun, Fan Cheng, Haiping Ma, Xiaoyan Sun |
| 2020 | ICDM | Quality meets Diversity: A Model-Agnostic Framework for Computerized Adaptive Testing. | Haoyang Bi, Haiping Ma, Zhenya Huang, Yu Yin, Qi Liu, Enhong Chen, Yu Su, Shijin Wang |
| 2020 | ICDM | Structure-based Knowledge Tracing: An Influence Propagation View. | Shiwei Tong, Qi Liu, Wei Huang, Zhenya Huang, Enhong Chen, Chuanren Liu, Haiping Ma, Shijin Wang |
| 2020 | SIGIR | Convolutional Knowledge Tracing: Modeling Individualization in Student Learning Process. | Shuanghong Shen, Qi Liu, Enhong Chen, Han Wu, Zhenya Huang, Weihao Zhao, Yu Su, Haiping Ma, Shijin Wang |
| 2019 | CIKM | DIRT: Deep Learning Enhanced Item Response Theory for Cognitive Diagnosis. | Song Cheng, Qi Liu, Enhong Chen, Zai Huang, Zhenya Huang, Yiying Chen, Haiping Ma, Guoping Hu |
| 2019 | KDD | Exploiting Cognitive Structure for Adaptive Learning. | Qi Liu, Shiwei Tong, Chuanren Liu, Hongke Zhao, Enhong Chen, Haiping Ma, Shijin Wang |
| 2018 | CEC | A Novel Binary Jaya Optimization for Economic/Emission Unit Commitment. | Zhile Yang, Yuanjun Guo, Qun Niu, Haiping Ma, Yimin Zhou, Li Zhang |
| 2017 | CIKM | An Ad CTR Prediction Method Based on Feature Learning of Deep and Shallow Layers. | Zai Huang, Zhen Pan, Qi Liu, Bai Long, Haiping Ma, Enhong Chen |
| 2016 | ICDM | Sparse Factorization Machines for Click-through Rate Prediction. | Zhen Pan, Enhong Chen, Qi Liu, Tong Xu, Haiping Ma, Hongjie Lin |
| 2015 | KSEM | Mining User's Location Intention from Mobile Search Log. | Yifan Sun, Xin Li, Lin Li, Qi Liu, Enhong Chen, Haiping Ma |
| 2013 | CIS | Random Walk with Pre-filtering for Social Link Prediction. | Ting Jin, Tong Xu, Enhong Chen, Qi Liu, Haiping Ma, Jingsong Lv, Guoping Hu |
| 2012 | CEC | Biogeography-based optimization with ensemble of migration models for global numerical optimization. | Haiping Ma, Minrui Fei, Zhiguo Ding, Jing Jin |
| 2012 | WWW | A habit mining approach for discovering similar mobile users. | Haiping Ma, Huanhuan Cao, Qiang Yang, Enhong Chen, Jilei Tian |
| 2010 | GECCO | Biogeography-based optimization with blended migration for constrained optimization problems. | Haiping Ma, Dan Simon |