武慧

中文 English 教学 新建主栏目 基本信息 名称 武慧，哈尔滨工业大学（威海）经济管理学院副教授。2018年于山东大学数学学院获得统计学学士学位，2022年于清华大学工业工程系获得管理科学与工程博士学位。研究方向包括基于统计学习方法和人工智能方法的大规模复杂系统建模、在线监控、异常检测、故障预测和健康管理。她在国际权威期刊如《IISE Transactions》、《IEEE Transactions on Neural Networks and Learning Systems》、《IEEE Transactions on Industrial Informatics》、《Technometrics》、《Reliability Engineering and System Safety》、《IEEE Transactions on Automation Science and Engineering》发表多篇论文；参与编写教材《机器学习与大数据分析》；参与完成国家自然科学基金重点项目《大数据驱动的高速铁路高可用性研究》、清华-华为合作项目《装备SDS效率提升技术》、清华大学本科教学改革项目《本科优秀教材建设》等；此外，多项学术成果在美国管理科学与运筹学会（INFORMS）、国际工业与系统工程学会（IISE）、中国优选法统筹法与经济数学研究会等国内外权威学会年会获奖。 课题组常年有招收计划，欢迎自律并热爱科研、数学基础优秀、擅长编程的高年级同学发送简历至 wuh@hit.edu.cn 教育经历 标题 起讫时间 2018年9月——2022年10月 所学专业 管理科学与工程 学习机构 清华大学 工业工程系 学历 博士 简单介绍 标题 起讫时间 2014年9月——2018年7月 所学专业 统计学 学习机构 山东大学 数学学院 学历 学士 简单介绍 工作经历 标题 工作单位 哈尔滨工业大学（威海） 职位/职称 副教授 起讫时间 2023年3月——现在 简单介绍 研究领域 名称 1. 工业大数据建模, 质量管理, 统计过程监控 2. 复杂工业大数据驱动下的系统可靠性分析，故障预测与健康管理 3. 智能互联系统的统计建模、预测以及智能决策 所获奖励 奖项名称 2022 首届粤港澳大湾区（黄埔） 国际算法算例大赛（工业品表面缺陷检测技术）三等奖 获奖时间 完成人 所获奖项 简单介绍 奖项名称 2021 国际工业与系统工程学会（IISE）数据分析与信息系统（DAIS）分会最佳学生论文第一名 获奖时间 完成人 所获奖项 简单介绍 奖项名称 2021 美国管理科学与运筹学会（INFORMS）质量统计可靠性(QSR)分会最佳学生论文入围奖(Finalist) 获奖时间 完成人 所获奖项 简单介绍 奖项名称 2020 研究生国家奖学金 获奖时间 完成人 所获奖项 简单介绍 奖项名称 2020 三菱重工奖学金 获奖时间 完成人 所获奖项 简单介绍 奖项名称 2019 全国工业工程博士生学术论坛优秀会议论文奖 获奖时间 完成人 所获奖项 简单介绍 奖项名称 2019 中国优选法统筹法与经济数学研究会工业工程分会学术交流暨学会年会最佳论文奖 获奖时间 完成人 所获奖项 简单介绍 科研项目 名称 6. 2023.09-2025.12：韧性城市建设背景下新型交通基础设施运维管理体系及路径研究，哈工大哲学社会科学高质量发展行动计划重点项目（HIT.HSS.202323），主持 5. 2023.09-2025.12：质量大数据背景下面向智慧城市复杂系统的智能预警方法研究，哈尔滨工业大学（威海）青年教师发展基金项目，主持 4. 2020.12-2022.06：本科优秀教材建设（机器学习与大数据分析），清华大学本科教学改革项目，参与 3. 2018.01-2022.12：大数据驱动的高速铁路高可用性研究，国家自然科学基金重点项目(71731008)，参与 2. 2019.12-2022.12：基于数字孪生技术的城轨列车走行系统故障预测与健康管理，北京市自然科学基金-轨道交通联合基金项目(L191022)，参与 1. 2018.11-2019.07：装备SDS测试效率提升，华为机器有限公司，参与 期刊论文 名称 1. H. Wu and Y.F. Li*. 2023. A Multi-Sensor Fusion-based Prognostics Model for Systems with Partially Observable Failure Modes. IISE Transaction. DOI: 10.1080/24725854.2023.2222402. 2. H. Wu and Y.F. Li*. 2023. Adaptive Graph-Based Support Vector Data Description for Weakly-Supervised Anomaly Detection. IEEE Transactions on Automation Science and Engineering. DOI: 10.1109/TASE.2023.3288111. 3. M. Qian, H. Wu and Y. -F. Li*.2022. Wind Turbine Blade Early Fault Detection with Faulty Label Unknown and Labeling Bias. IEEE Transactions on Industrial Informatics. DOI: 10.1109/TII.2022.3216816. 4. H. Wu and Y.F. Li*. 2022. Clustering Spatially Correlated Functional Data with Multiple Scalar Covariates. IEEE Transactions on Neural Networks and Learning Systems. DOI: 10.1109/TNNLS.2021.3137795. 5. H. Wu, C. Zhang and Y.F. Li*. 2021. Monitoring Heterogeneous Multivariate Profiles Based on Heterogeneous Graphical Model. Technometrics. 64:2, 210-223. 6. H. Wu, Y.F. Li* and C. Bérenguer. 2020. Optimal Inspection and Maintenance for a Repairable k-out-of-n: G Warm Standby System. Reliability Engineering and System Safety. 193, 106669. 7. H. Wu. Multi-Task Clustering and Variable Selection for Mixed-Type Skewed Data. Revision. 8. H. Wu. A Functional Competing Risk Model for Multisensor Fusion and RUL Prediction with Missing Failure Causes. Revision. 9. H. Wu. A Functional Label Noise Model for Early Fault Detection and Diagnosis. Submitted. 10. H. Wu and Y.F. Li. Spatio-temporal Reliability Modelling for Cellular Mobile Networks.Underworking. 11. H. Wu and Y.F. Li. Adaptive Robust Functional Mixture Model for Monitoring Image Data with Application to Two-photon Lithography. Underworking. 授权专利 名称 1. 李彦夫，武慧，刘乐.基于PCA和多维监测数据的主板异常诊断方法及装置： CN202010148302.9[P]. 2020-07-07. Basic Information 名称 Hui Wu is an associate professor at the School of Economics and Management, Harbin Institute of Technology (Weihai). She received a B.S. degree in statistics from Shandong University, Jinan, China, in 2018, and a Ph.D. degree in management science and engineering from Tsinghua University, Beijing, China, in 2022. Her current research focuses on developing statistical learning and artificial intelligence methods for large-scale complex system modeling, online monitoring, anomaly detection, and reliability analysis. Education 名称 Tsinghua University, China 2018-2022 Ph.D. in Management Science and Engineering Shandong University, China 2014-2018 BS in Statistics Work Experience 名称 Harbin Institute of Technology, Weihai, China 2023-Present Associate Professor with the School of Economics and Management Research Fields 名称 Industrial big data modeling, quality management, statistical process control System reliability analysis, prognostics and health management Statistical modeling, prediction, and intelligent decision-making for intelligent interconnection systems Scholarships/Awards 名称 IISE DAIS Best Student Paper Award, 2021 INFORMS QSR Best Student Paper Finalist, 2021 Chinese National Scholarship for Graduate Students, 2020 Mitsubishi Scholarship, 2019 Outstanding Conference Paper Award of National Academic Forum for Doctoral Students in Industrial Engineering, 2019 CSOOPEM IE Best Student Paper Award, 2019 Third Prize in the International Algorithm and Example Contest for Industrial Product Surface Defect Detection Technology, Guangdong-Hong Kong-Macao Greater Bay Area (Huangpu), 2023 Research Projects 名称 2023.09-2025.12: "Research on the Operation and Maintenance Management System and Path of Innovative Transportation Infrastructure in the Context of Resilient City Construction", Key Project of the Action Plan for High-Quality Development of Philosophy and Social Sciences of HIT, HIT.HSS.202323. (PI). 2023.09-2025.12: "Research on Intelligent Early Warning Methods for Complex Systems of Smart Cities in the Context of Big Quality Data", Harbin Institute of Technology (Weihai) Young Teachers' Development Fund Program. (PI). 2020.12-2022.06: ”Undergraduate Excellent Textbook Construction (Machine Learning and Big Data Analytics)”, Tsinghua University Undergraduate Teaching Reform Project. (Participant). 2018.01-2022.12: “Big-data Driven Methodologies for High Availability of the High-speed Railways”, National Natural Science Foundation of China (NSFC), Key project 71731008. (Participant). 2019.01-2022.12, "Prognostics and health management of the railway vehicle running gears based on digital-twin technology ", Beijing Municipal Natural Science Foundation-Rail Transit Joint Research Program, L19102. (Participant). 2018.11-2019.07: “SDS Reliability Testing Efficiency Optimization”, Huawei Machine Ltd. (Participant). Journal Papers 名称 1. H. Wu and Y.F. Li*. 2023. A Multi-Sensor Fusion-based Prognostics Model for Systems with Partially Observable Failure Modes. IISE Transaction. DOI: 10.1080/24725854.2023.2222402. 2. H. Wu and Y.F. Li*. 2023. Adaptive Graph-Based Support Vector Data Description for Weakly-Supervised Anomaly Detection. IEEE Transactions on Automation Science and Engineering. DOI: 10.1109/TASE.2023.3288111. 3. M. Qian, H. Wu and Y. -F. Li*.2022. Wind Turbine Blade Early Fault Detection with Faulty Label Unknown and Labeling Bias. IEEE Transactions on Industrial Informatics. DOI: 10.1109/TII.2022.3216816. 4. H. Wu and Y.F. Li*. 2022. Clustering Spatially Correlated Functional Data with Multiple Scalar Covariates. IEEE Transactions on Neural Networks and Learning Systems. DOI: 10.1109/TNNLS.2021.3137795. 5. H. Wu, C. Zhang and Y.F. Li*. 2021. Monitoring Heterogeneous Multivariate Profiles Based on Heterogeneous Graphical Model. Technometrics. 64:2, 210-223. 6. H. Wu, Y.F. Li* and C. Bérenguer. 2020. Optimal Inspection and Maintenance for a Repairable k-out-of-n: G Warm Standby System. Reliability Engineering and System Safety. 193, 106669. 7. H. Wu. Multi-Task Clustering and Variable Selection for Mixed-Type Skewed Data. Revision. 8. H. Wu. A Functional Competing Risk Model for Multisensor Fusion and RUL Prediction with Missing Failure Causes. Revision. 9. H. Wu. A Functional Label Noise Model for Early Fault Detection and Diagnosis. Submitted. 10. H. Wu and Y.F. Li. Spatio-temporal Reliability Modelling for Cellular Mobile Networks.Underworking. 11. H. Wu and Y.F. Li. Adaptive Robust Functional Mixture Model for Monitoring Image Data with Application to Two-photon Lithography. Underworking. Patent 名称 Y.F. Li, H. Wu and L. Liu. 2020. Anomaly Diagnosis Method and Device for Motherboard based on PCA and Multidimensional Data: CN202010148302.9[P]. 2020-07-07. 讲授课程 名称 大数据思维与创新应用 多元统计与R建模 人工智能与机器学习