吴迪

2022-10-24 09:54 作者: 审核: 浏览:

姓名:

吴迪

性别:

学历:

博士

职称:

教授

部门:

 计算机与信息科学学院 软件学院

计算机科学系

邮件地址:

wudi1986@swu.edu.cn wudi.cigit@gmail.com

研究方向:

数据挖掘,机器学习,隐私计算,人工智能

个人主页

https://wudi1989.github.io/Homepage/

个人简介

吴迪,工学博士,教授,博导,西南大学含弘研究员,中科院西部青年学者,美国路易斯安娜大学拉法叶分校访问学者,研究聚焦不完备流数据智能计算。主持国家自然科学基金面上和青年项目各1项、中科院人才项目1项、省部级项目4项、横向3项,累积负责科研经费500余万元;第一/通讯作者发表IEEE Transactions汇刊论文和AAAIIEEE ICDM会议论文16、中科院一区论文3篇,其中包括中国计算机学会推荐CCF-A7篇、ESI热点论文1篇、ESI高被引论文2篇,唯一作者出版英文专著一本(Springer出版社)SCI统计引用1300余次,谷歌学术统计引用2400余次、H指数27,引用学者包括两院院士、发达国家院士、国家杰青/长江、AAAS/IEEE/ Fellow30人次;国际期刊Neurocomputing(中科院二区Top, CCF-C)Frontiers in Neurorobotics(SCI, IF 3.1)副编辑;获授权发明专利7项、软件著作权1项,参编行业标准1项、学术专著1本;获中国人工智能学会优秀博士论文提名奖、重庆市优秀博士学位论文、中国科学院院长优秀奖、首届川渝科技学术大会优秀论文三等奖(1/5);研究成果在能源电力领域开展真实应用,每年产生间接经济效益超过2000万元。

所属团队为“图与社会计算”,团队由罗辛教授领衔(国家级青年人才、二级教授),欢迎各位立志做科研、具有主观能动性、能吃苦耐劳的本科、硕士、博士同学加入团队。团队介绍见http://cis.swu.edu.cn/info/1037/2188.htm

教学情况

  教授课程《智能决策分析》,主要从图学习的角度出发介绍如何针对图数据开展图表示学习和智能决策,包括图学习的基本概念、基本分析方法和最新相关研究进展。

科研情况

一、主持项目 

[1] 2023.01-2024.12全球煤油气电耦合下我国能源安全风险识别与战略路径优化技术研究 国家电网总部科技项目 120/407 主持

[2] 2022.01-2025.12国家自然科学基金面上项目 58万元 主持

[3] 2018.01-2020.12国家自然科学基金青年基金 24万元 主持

[4] 2020.03-2022.12中国科学院西部青年学者 15万元 主持

[5] 2019.08-2021.12重庆市自然科学基金面上项目 10万元 主持

[6] 2016.01-2016.12重庆市应用开发计划项目课题 重庆市科技局 75.5万元主持

[7] 2020.06-2020.12能源战略演变模型开发研究 国网能源研究院有限公司59万元 主持

[8]2022.06-2022.12基干多源信息融合的人工智能负荷预测技术研究 国网南通供电公司 16.17万元 主持


二、代表成果

[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, vol. 34, no. 6, pp. 2525-2538, 2022. (CCF-A期刊,中科院一区,IF 8.9, ESI热点/高引论文)

[2] Di Wu, Shengda Zhuo, Yu Wang, Zhong Chen, and Yi He, Online Semi-Supervised Learning with Mix-Typed Streaming Features, Thirty-Seventh AAAI Conference on Artificial Intelligence, AAAI 2023 (CCF-A会议,Accept rate 19.6%)

[3] Di Wu, Bo Sun, and Mingsheng Shang, Hyperparameter Learning for Deep Learning-based Recommender Systems, IEEE Transactions on Services Computing, 2023, doi: 10.1109/TSC.2023.3234623. (CCF-A期刊中科院一区IF 8.1)

[4] Di Wu, Peng Zhang, Yi He, and Xin Luo, A Double-Space and Double-Norm Ensembled Latent Factor Model for Highly Accurate Web Service QoS Prediction, IEEE Transactions on Services Computing, 2022, doi: 10.1109/TSC.2022.3178543 (CCF-A期刊中科院一区IF 8.1)

[5] Di Wu, Qiang. He, Xin. Luo, Mingsheng. Shang, Yi. He, and Guoyin. Wang, A posterior-neighborhood-regularized latent factor model for highly accurate web service QoS prediction, IEEE Transactions on Services Computing, vol. 15, no. 2, pp. 793-805, 2022. (CCF-A期刊中科院一区IF 8.1, ESI高引论文)

[6] Di Wu, Xin Luo, Yi He, and MengChu Zhou, A Prediction-sampling-based Multilayer-structured Latent Factor Model for Accurate Representation of High-dimensional and Sparse Data, IEEE Transactions on Neural Networks and Learning Systems, 2022, 10.1109/TNNLS.2022.3200009. (中科院一区, CCF-B期刊, IF 10.4)

[7] Di Wu, Mingsheng Shang, Xin Luo, and Zidong. Wang, An L₁-and-L₂-Norm-Oriented Latent Factor Model for Recommender Systems, IEEE Transactions on Neural Networks and Learning Systems, vol. 33, no. 10, pp. 5775-5788, 2022. doi: 10.1109/TNNLS.2021.3071392. (中科院一区, CCF-B期刊, IF 10.4)

[8] Di Wu, Yi He, Xin Luo, and MengChu Zhou, A Latent Factor Analysis-based Approach to Online Sparse Streaming Feature Selection, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2021, DOI: 10.1109/TSMC.2021.3096065 (中科院一区, CCF-B期刊IF 8.7)

[9] 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, vol. 51, no. 7, pp. 4285-4296, 2021. (中科院一区, CCF-B期刊, IF 8.7, ESI高引论文)

[10] 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, vol. 8, no. 4, 2021. (中国科技期刊卓越行动计划世界一流重点建设期刊, IF=11.8,中科院一区)

[11] Di Wu, Yi He, and Xin Luo, A Graph-incorporated Latent Factor Analysis Model for High-dimensional and Sparse Data, Transactions on Emerging Topics in Computing, 2023, DOI: 10.1109/TETC.2023.3292866. (中科院二区IF 5.9)

[12] 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, IF 12.3)

[13] 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. (长文, 接受率9.8%, CCF-B会议core-rank A*)

[14] Dianlong You, Jiawei Xiao, Yang Wang, Huigui Yan, Di Wu*, Zhen Chen, Limin Shen, and Xindong Wu, Online Learning from Incomplete and Imbalanced Data Streams, IEEE Transactions on Knowledge and Data Engineering, 2023, DOI: 10.1109/TKDE.2023.3250472. (CCF-A期刊中科院一区IF 8.9, *Corresponding Author)

[15] Song Deng, Yujia Zhai, Di Wu*, Dong Yue, Xiong Fu, and Yi He, "A Lightweight Dynamic Storage Algorithm with Adaptive Encoding for Energy Internet", IEEE Transactions on Services Computing, 2023, doi: 10.1109/TSC.2023.3262635. (CCF-A期刊,中科院一区,IF 8.1*Corresponding Author)

[16] Song Deng, Jiantang Zhang, Di Wu*, Yi He, Xiangpeng Xie, and Xindong Wu, A Quantitative Risk Assessment Model for Distribution Cyber Physical System under Cyber Attack, IEEE Transactions on Industrial Informatics, 2022. DOI: 10.1109/TII.2022.3169456. (中科院一区, IF 12.3, *Corresponding Author)

[17] Teng Huang, Cheng Liang, Di Wu*, and Yi He, "A Debiasing Autoencoder for Recommender System," IEEE Transactions on Consumer Electronics, 2023, doi: 10.1109/TCE.2023.3281521.(*Corresponding Author, IF 4.414, 中科院二区)

[18] Dianlong You, Shina Niu, Siqi Dong, Huigui Yan, Zhen Chen, Di Wu*, Limin Shen, and Xindong Wu, Counterfactual explanation generation with minimal feature boundary, Information Sciences, vol 625, pp.342-366, 2023. (CCF-B期刊中科院一区, IF 8.1, *Corresponding Author)

[19] Dianlong You, Siqi Dong, Shina Niu, Huigui Yan, Zhen Chen, Shunfu Jin, Di Wu*, Xindong Wu, Local causal structure learning for streaming features, Information Sciences, vol 647, pp.119502, 2023. (*Corresponding Author, IF 8.1, 中科院一区, CCF-B)

[20] Cheng Liang, Di Wu*, Yi He, Teng Huang, Zhong Chen, and Xin Luo, MMA: Multi-Metric-Autoencoder for Analyzing High-Dimensional and Incomplete Data, European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML-PKDD 2023. (CCF-B会议Accept rate 24%,*Corresponding Author)

[21] Bo Sun, Di Wu*, Mingsheng Shang, and Yi He, Toward Auto-learning Hyperparameters for Deep Learning-based Recommender Systems, International Conference on Database Systems for Advanced Applications. Springer, Cham, 2022. (CCF-B会议*Corresponding Author)

[22] 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, IF 6)

[23] 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, IF 6.9)

[24]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. (CCF-C会议, 接受率24.1%core-rank A)


获奖情况

[1]        中国人工智能学会优秀博士论文提名奖,2021年度

[2]        重庆市优秀博士学位论文,2020年度

[3]        首届川渝科技学术大会优秀论文,三等奖,2020年度

备注

[1]        国际学术期刊Neurocomputing(中科院SCI二区TopIF 5.779)副编辑

[2]        国际学术期刊Frontiers in Neurorobotics(中科院SCI三区,IF 3.493)副编辑

[3]        国际会议IEEE ICDM 2023(CCF-B)关于Incomplete Streaming Data Analysis (ISDA 2023) Workshop的组织主席

[4]        20余个国际SCI学术期刊的特邀审稿人,包括IEEE TNNLSTSCTSMCTITSTCSSTHMSTIIJAS

[5]        国际会议AAAI 2023 (CCF-A)ECML-PKDD 2021-2023 (CCF-B)的程序委员