重庆市优秀博士论文，2020； 

中国科学院院长优秀奖，2018； 

中国科学院重庆绿色智能技术研究院优秀员工，2013，2017； 

[1]      Di Wu, Xin Luo, Mingsheng Shang, Yi He, Guoyin. Wang, and Xindong Wu, A Data-Characteristic-Aware Latent Factor Model for Web Service QoS Prediction, IEEE Transactions on Knowledge and Data Engineering, 2020, doi: 10.1109/TKDE.2020.3014302. (CCF推荐A类期刊) 

[2]      Di Wu and Xin Luo, Robust Latent Factor Analysis for Precise Represen-tation of High-dimensional and Sparse Data, IEEE/CAA Journal of Automatica Sinica, 2020. DOI: 10.1109/JAS.2020.1003533. (中国科技期刊卓越行动计划世界一流重点建设期刊，中科院二区) 

[3]      Di Wu, Long Jin, and Xin Luo, PMLF: Prediction-Sampling-based Multilayer-Structured Latent Factor Analysis, In proceeding of the 2020 IEEE International Conference on Data Mining, ICDM, 2020. (Regular paper, 接受率9.8%, CCF推荐B类会议) 

[4]      Di. Wu, Qiang. He, Xin. Luo, Mingsheng. Shang, Yi. He, and Guoyin. Wang, “A posteriorneighborhood-regularized latent factor model for highly accurate web service QoS prediction,” IEEE Transactions. on Services Computing, 2019, DOI:10.1109/TSC.2019.2961895 (中科院一区) 

[5]      Di Wu, Xin Luo, Mingsheng Shang, Yi He, Guoyin Wang, and MengChu Zhou, A Deep Latent Factor Model for High-Dimensional and Sparse Matrices in Recommender Systems, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2019, DOI:10.1109/TSMC.2019.2931393 (中科院一区) 

[6]      Di Wu, Xin Luo, Mingsheng Shang, Yi He, Guoyin Wang, and Xindong Wu, Online Feature Selection with Capricious, In proceeding of the 2019 IEEE international conference on big data, Bigdata, 2019, Los Angeles, CA, USA, 2019.12.9-2019.12.12. (EI, CCF推荐会议) 

[7]      Di Wu, Xin Luo, Mingsheng Shang, Yi He, Guoyin Wang, and Xindong Wu, A Data-Aware Latent Factor Model for Web Service QoS Prediction, In proceeding of the 23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD, 2019, Macau, China, 2019.4.14-2019.4.17. (EI, CCF推荐会议) 

[8]      Di Wu, Xin Luo, Guoyin Wang, Mingsheng Shang*, Ye Yuan, and Huyong Yan, A Highly-Accurate Framework for Self-Labeled Semi-Supervised Classification in Industrial Applications, IEEE Transactions on Industrial Informatics, 2018, 14 (3): 909-920. (中科院一区) 

[9]      Di Wu, Minsheng Shang, Xin Luo, Ji Xu, Huyong Yan, Weihui Deng, and Guoyin Wang, Self-training semi-supervised classification based on density peaks of data, Neurocomputing, 2018, 275:180-191. (中科院二区) 

[10] Di Wu, Huyong Yan, Mingsheng Shang, Kun Shan, and Guoyin Wang, Water eutrophication evaluation based on semi-supervised classification: A case study in Three Gorges Reservoir, Ecological Indicators, 2017, 81: 362-372. (中科院二区) 

[1]  国家自然科学基金青年基金项目，61702475，面向富营养化评价的动态自标记半监督分类模型研究，2018.01-2020.12，24万元，主持； 

[2]  面向富营养化评价的深度隐特征分析技术研究，重庆市自然科学基金面上项目，cstc2019jcyj-msxmX0578，10万元，2019.08-2021.12，主持； 

[3]  深度隐特征分析技术研究，中科院西部之光青年学者B，15万元，2020.01-2022.12，主持； 

[4]  能源战略演变模型开发研究，国网能源研究院有限公司委托项目，59万元，2020.06-2020.12，主持