Nengjun Zhu, Yuqiang Ren, Yu Liu, Hang Yu, Xinzhi Wang, and Xiangfeng Luo, MMGCL: Multi-Scale and Multi-Channel Graph Contrastive Learning for Flight Anomaly Detection, Knowledge-Based Systems, 2025, SCI, IF7.6, 中科院1区
Qiqi Cai, Jian Cao, and Guandong Xu, and Nengjun Zhu, Distributed Recommendation Systems: Survey and Research Directions, ACM Transactions on Information Systems, 2024,43(1), SCI, IF6, CCF-A刊
Zixuan Yuan, Junmin Liu, Haoyi Zhou, Denghui Zhang, Hao Liu, Nengjun Zhu, and Hui Xiong, LEVER: Online Adaptive Sequence Learning Framework for High-Frequency Trading, IEEE Transactions On Knowledge And Data Engineering (TKDE), 2023, 36(11), 6547-6559, SCI, IF8.9, 中科院2区, CCF-A刊
Nengjun Zhu, Jian Cao*, Xinjiang Lu, Chuanren Liu, Hao Liu, Yanyan Li, Xiangfeng Luo, and Hui Xiong, Predicting a Person's Next Activity Region with a Dynamic Region-Relation-Aware Graph Neural Network, ACM Transactions on Knowledge Discovery from Data (TKDD), 2022, 16(2), 116: 1-23, SCI, IF4.4, 中科院3区，CCF-B刊
Nengjun Zhu, Jian Cao, Xinjiang Lu, Hui Xiong, Learning a Hierarchical Intent Model for Next-Item Recommendation, ACM Transactions on Information Systems (TOIS). 2021. vol. 40, no. 2, article 38, pp. 1-28, CCF-A期刊
Nengjun Zhu, Jian Cao, Kunwei Shen, Xiaosong Chen, and Siji Zhu, A Decision Support System with Intelligent Recommendation for Multi-Disciplinary Medical Treatment, ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM). ACM, 2020. vol. 16, no. 1s, 33, pp1-23, CCF-B期刊
Nengjun Zhu*, Lingdan Sun, Qi Zhang, Jian Cao, Hang Yu, DFRec: Dual Fluctuation Modeling of Multi-level Intent Evolution for Next-Item Recommendation, Proceedings of the AAAI, 2026, CCF-A会
Nengjun Zhu*, Zhiyu Zhang, Chenmeijin Liang, Jian Cao, Siji Zhu*, and Xiao Wei, Trusted Collective Learning for Conflictive Multi-View Decision-Making, Proceedings of the IEEE International Conference on Data Mining (ICDM), 2025, CCF-B会，最佳论文提名
Yang Gu, Jian Cao*, Hengyu You, Nengjun Zhu*, and Shiyou Qian, ADELA: Accelerating Evolutionary Design of Machine Learning Pipelines with the Accompanying Surrogate Model, Proceedings of the AAAI, 2025, 16915-16923, EI, CCF-A会
Jianqi Gao, Jiao Cao, and Nengjun Zhu, Promoting Knowledge Base Question Answering by Directing LLMs to Generate Task-relevant Logical Forms, Proceedings of the AAAI, 2025, CCF-A会
Shouyu Chen, Tangwei Ye, Laizhong Yuan, Qi Zhang, Ke Liu, Usman Naseem, Ke Sun, Nengjun Zhu, and Liang Hu, VR-DiagNet: Medical Volumetric and Radiomic Diagnosis Networks with Interpretable Clinician-like Optimizing Visual Inspection, Proceedings of the 32nd ACM International Conference on Multimedia (MM), 2024, 10459-10467, EI, CCF-A会
Nengjun Zhu*, Jieyun Huang, Jian Cao, Liang Hu, Zixuan Yuan, and Huanjing Gao, R2V-MIF: Rule-to-Vector Contrastive Learning and Multi-channel Information Fusion for Therapy Recommendation, Proceedings of International Joint Conference on Artificial Intelligence (IJCAI), 2024, 2634-2641, EI, CCF-A会
Haoran Xin, Xinjiang Lu, Nengjun Zhu, Tong Xu, Dejing Dou, and Hui Xiong, CAPTOR: A Crowd-Aware Pre-Travel Recommender System for Out-of-Town Users, Proceedings of the ACM International Conference on Research and Development in Information Retrieval (SIGIR), 2022, 1174-1184, EI, CCF-A会
Nengjun Zhu, Jian Cao, Yanchi Liu, Yang Yang, Haochao Ying, and Hui Xiong, Sequential Modeling of Hierarchical User Intention and Preference for Next-item Recommendation, in Proceedings of the ACM International Conference on Web Search and Data Mining (WSDM). ACM, 2020. pp807-815, CCF-B会，清华推荐A会
