科研情况 主持的科研项目： [1] 重庆市技术创新与应用发展重点项目，多模态数据融合驱动的经济作物垂直模型研发，2025/01-20217/12，200万，主持 [2] 重庆市教委科学技术研究项目重点项目，基于高阶图神经网络的学生学习认知诊断模型研究，2024/09-2027/09，8万，主持 [3] 国家自然科学基金青年项目，基于张量低秩学习的异质信息网络表示方法研究，2024/01-2026/12，30万，主持 [4] 重庆市教委科学技术研究项目青年项目，基于张量网络的大规模电网动态演化建模方法研究，2023/09-2026/09，4万，主持 参与的科研项目： [1] 国家自然科学基金面上项目，面向海绵城市运维大数据的高维稀疏张量分析方法研究，2021-01-01至 2024-12-31, 56万, 参与 [2] 国家自然科学基金面上项目, 62272078, 大规模属性异质图张量低秩学习方法, 2023-01-01至 2026-12-31, 54万元, 参与 [3] 国家自然科学基金青年科学基金项目, 61802360, 基于医疗大数据的阿尔茨海默病症状发展预测模型, 2019-01-01 至 2021-12-31, 27万元, 参与 近五年的代表性论文： [1] Hao Wu, Yan Qiao, and Xin Luo*. A Fine-Grained Regularization Scheme for Nonnegative Latent Factorization of High-Dimensional and Incomplete Tensors. IEEE Transactions on Services Computing, DOI:10.1109/TSC.2024.34861712024, 2024. CCF-A类 [2] Hao Wu, Lei Yang, and Zhetao Zhang. Latent Factorization of Tensors in Hyperbolic Space for Spatiotemporal Traffic Data Imputation. IEEE/CAA Journal of Automatica Sinica (中国科技期刊卓越行动计划世界一流重点建设期刊). DOI：10.1109/JAS.2024.124911, 2024. 中科院一区 [3] Peng Tang, Tao Ruan, Hao Wu*, and Xin Luo. Temporal pattern-aware QoS prediction by Biased Non-negative Tucker Factorization of tensors. Neurocomputing, 2024, 582: 127447. 中科院二区 [4] A. Zeng and Hao Wu*. A Fast and Inherently Nonnegative Latent Factorization of Tensors Model for Dynamic Directed Network Representation, In Proc. of the 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD), Tianjin, China, 2024, pp. 2955-2960. [5] Q. Wang and Hao Wu*. Dynamically Weighted Directed Network Link Prediction Using Tensor Ring Decomposition, In Proc. of the 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD), Tianjin, China, 2024, pp. 2864-2869. [6] Hao Fang, Qu Wang, Qicong Hu, and Hao Wu*. Modularity Maximization-Incorporated Nonnegative Tensor RESCAL Decomposition for Dynamic Community Detection, In Proc. of the 2024 IEEE Int. Conf. on Systems, Man, and Cybernetics. (SMC), Sarawak, Malaysia, 2024. [7] Xin Luo, Hao Wu, and Zechao Li*. NeuLFT: A Novel Approach to Nonlinear Canonical Polyadic Decomposition on High-Dimensional Incomplete Tensors. IEEE Transactions on Knowledge and Data Engineering. 2023, 35(6): 6148-6166. CCF-A类，ESI高被引 [8] Xin Luo, Hao Wu, Zhi Wang, Jianjun Wang, and Deyu Meng*. A Novel Approach to Large-Scale Dynamically Weighted Directed Network Representation. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2022, 44(12): 9756-9773. CCF-A类 中科院一区 ESI高被引 [9] Hao Wu, Xin Luo*, and MengChu Zhou. Advancing Non-negative Latent Factorization of Tensors with Diversified Regularizations. IEEE Transactions on Services Computing, 2022, 15(3): 1334-1344，CCF-A类 ESI高被引 [10] Hao Wu, Xin Luo*, MengChu Zhou*, Muhyaddin J. Rawa, Khaled Sedraoui, and Aiiad Albeshri. A PID-Incorporated Latent Factorization of Tensors Approach to Dynamically Weighted Directed Network Analysis. IEEE/CAA Journal of Automatica Sinica (中国科技期刊卓越行动计划世界一流重点建设期刊). 2022, 9(3): 533-546. 中科院一区 [11] Xin Luo, Minzhi Chen, Hao Wu, Zhigang Liu, Huaqiang Yuan, and MengChu Zhou. Adjusting Learning Depth in Non-negative Latent Factorization of Tensors for Accurately Modeling Temporal Patterns in Dynamic QoS Data, IEEE Transactions on Automation Science and Engineering, 2021, 18(4): 2142-2155. 中科院二区 [12] Hao Wu, and Xin Luo. Instance-Frequency-Weighted Regularized, Nonnegative and Adaptive Latent Factorization of Tensors for Dynamic QoS Analysis. In Proc. of the 2021 IEEE Int. Conf. on Web Services. (ICWS2021) (Regular), Chicago, IL, USA , 2021, pp. 560-568. CCF B类 [13] Xin Luo#, Hao Wu#, MengChu Zhou* and Huaqiang Yuan*. Temporal Pattern-aware QoS Prediction via Biased Non-negative Latent Factorization of Tensors. IEEE Transactions on Cybernetics, 2020, 50(5): 1798-1809. 中科院一区，ESI高被引 出版专著 Hao Wu, Xuke Wu, Xin Luo. Dynamic Network Representation Based on Latent Factorization of Tensors. Springer, 2023. (https://link.springer.com/book/10.1007/978-981-19-8934-6) |
