姓名：邵伟明

系属：化工装备与控制工程系

学位：博士研究生

职称：副教授

专业：控制理论与控制工程

导师类别：博导、硕导

电子邮箱：shaoweiming@upc.edu.cn

通讯地址：山东省青岛市黄岛区长江西路66号

课题组主页：https://www.labxing.com/-epebdal

·         ※ 研究方向

能源过程装备大数据分析与应用

※ 教育经历

2010.9-2016.6，kaiyun体育登录网页入口（华东）自动化系，研究生（博士）

2014.11-2015.11，哈里法科技大学（原阿布扎比石油学院），电气工程系访问学者

2005.9-2009.7，kaiyun体育登录网页入口（华东）自动化系，本科（学士）

·         ※ 工作经历

2020.1至今，kaiyun体育登录网页入口（华东）新能源学院装控系，博士生导师

2019.12至今，kaiyun体育登录网页入口（华东）新能源学院装控系，副教授，硕士生导师

2017.3-2019.11，浙江大学控制科学与工程学院，博士后

2016.7-2017.2，青岛鼎信通讯股份有限公司，研发工程师

·         ※ 主讲课程

本科生课：控制工程基础、过程装备控制技术、专业实习

研究生课：现代控制理论、能源化工装备技术新进展

·         ※ 学术兼职

1. 中国机械工程学会高级会员、工业大数据与智能系统分会委员

2. 中国自动化学会数据驱动控制、学习与优化专业委员会委员

·         ※ 招收研究生方向

1. 机器学习、统计学习、深度学习等工业大数据分析理论与方法

2. 工业过程与设备的关键性能指标在线智能感知、故障智能分类与诊断

3. 能源过程与装备数字孪生、智能装备

·         ※ 承担科研项目

1. 国家自然科学基金面上项目（主持）：石化过程产品质量指标分布式软测量方法研究与应用验证，2022.01-2025.12，62173344

2. 国家自然科学基金青年基金项目（主持）：基于半监督集成学习的化工过程自适应软测量建模方法研究2018.1-2020.12，61703367

3. 中国博士后科学基金特别资助项目（主持）：基于概率模型的连铸坯皮下夹渣缺陷实时预报与诊断方法，2019.6-2019.11，2019T120516

4. 中国博士后科学基金面上项目（主持）：基于集成概率模型的半监督软测量建模方法研究,2017.11-2019.11，2017M621929

5. 中央高校基本科研业务费专项资金项目（主持）：大规模化工过程分布式建模与应用，2020.5-2022.4，20CX06010A

6. 工业控制技术国家重点实验室开放课题（主持）：大规模非高斯时序工业数据的分布式鲁棒建模及应用，2023.1-2023.12，ICT2023B10

7. 工业控制技术国家重点实验室开放课题（主持）：基于混合模型的动态过程产品质量鲁棒预测与监测方法研究，2021.1-2021.12，ICT2021B50

8. 国家自然科学基金重点基金项目（核心成员，5/18）：面向故障诊断的流程工业大数据分析与分布式建模方法2019.1-2023.12，61833014

·         ※ 获奖情况

1.中国循环经济协会科学技术进步三等奖，2023

2.第10届数据驱动控制与学习系统会议优秀论文提名奖，2021

3.第7届数据驱动控制与学习系统会议优秀论文提名奖，2018

4.第28届中国过程控制会议优秀张贴论文奖，2017

5. 指导员工获奖：

2024年本科生大创优秀结题（国家级）

第十四届过程装备与实践创新大赛一等奖

第十三届过程装备与实践创新大赛二等奖

中国光谷·华为杯第十九届中国研究生数学建模竞赛二等奖

“华数杯”全国老员工数学建模竞赛三等奖

“华为杯”第五届中国研究生人工智能创新大赛三等奖

“车谷杯”第九届中国研究生能源装备创新设计大赛三等奖

·         ※ 荣誉称号

2024年国家级创新大赛优秀指导教师

2023年过程装备与实践创新大赛优秀指导教师

2023 年kaiyun体育登录网页入口（华东）“十佳研究生导师团队”成员

2022年kaiyun体育登录网页入口（华东）“十佳百优”优秀班主任

·         ※ 出版教材

赵东亚，邵伟明，蒋秀珊，张兰.《过程装备控制技术》，中国石化出版社,2022

• ※ 发表论文

1.Weiming Shao, Xu Li, Yupeng Xing, et al. A mixture of shallow neural networks for virtual sensing: Could perform better than deep neural networks. Expert Systems With Applications, 2024 (SCI一区TOP)

2.Wenxue Han, Weiming Shao^*, Chihang Wei, et al. A novel semi-supervised robust learning framework for dynamic generative latent variable models and its application to industrial virtual metrology. Advanced Engineering Informatics, 2024 (SCI一区TOP)

3.Weiming Shao, Wenxue Han, Chuanfa Xiao, et al. Semi-Supervised Robust Hidden Markov Regression for Large-Scale Time-Series Industrial Data Analytics and Its Applications to Soft Sensing. IEEE Transactions on Automation Science and Engineering, 2024 (SCI二区TOP)

4.Guoqing Mu, Junghui Chen, Jingxiang Liu, Weiming Shao. Enhancing Predictive Monitoring of Ethylene Oxychlorination Reactor States through Spatiotemporal Coupling Analysis. Process Safety and Environmental Protection, 2024 (SCI二区TOP)

5.Yating Yao, Yupeng Xing, Ziteng Zuo, Chihang Wei, Weiming Shao^*. Virtual Sensing of Key Variables in the Hydrogen Production Process: A Comparative Study of Data-Driven Models, Sensors, 2024 (SCI三区)

6.Junxi Zhou, Xu Li, Weiming Shao^*, et al., A semi-supervised JITL paradigm based on manifold regularization for online soft sensor development. Asia-Pacific Journal of Chemical Engineering, 2024 (SCI四区)

7.Yating Yao, Xiaohang Shen, Linke Qiao, Ziteng Zuo, Weiming Shao^*, et al., Soft analyzer for sulfur content in tail oil of hydrocracking process based on adaptively regularized dynamic polynomial PLS. Asia-Pacific Journal of Chemical Engineering, 2024 (SCI四区)

8.Yougao Li, Wenxue Han, Weiming Shao^*, et al. Virtual sensing for dynamic industrial process based on localized linear dynamical system models with time-delay optimization. ISA Transactions, 2023 (SCI二区TOP)

9.Ping Wang, Yichao Yin, Junxi Zhou, Weiming Shao^*. A Semisupervised Just-In-Time Learning Framework Based on Local Label Propagation and Its Application to Industrial Virtual Sensing. IEEE Sensors Journal, 2023 (SCI二区)

10.Chuanfa Xiao, Wenxue Han, Weiming Shao^*, et al. Distributed Semisupervised HMM for Dynamic Inferential Sensor Development, IEEE Sensors Journal, 2023 (SCI二区)

11.Weiming Shao, Xu Li, Yating Yao, et al., Semi-supervised local manifold regularization model based on dual representation for industrial soft sensor development. Chemometrics and Intelligent Laboratory Systems, 2023 (SCI二区)

12.邵伟明,韩文学, 宋伟等. 基于分布式贝叶斯隐马尔可夫回归的动态软测量建模方法, 化工学报, 2023 (EI)

13.Jingxiang Liu, Guanyu Hou, Weiming Shao, Junghui Chen. A supervised functional Bayesian inference model with transfer-learning for performance enhancement of monitoring target batches with limited data. Process Safety and Environmental Protection, 2023 (SCI二区TOP)

14.Ziyun Yuan, Lei Chen, Gang Liu, Weiming Shao, et al. Physics-informed Student’s t mixture regression model applied to predict mixed oil length, Journal of Pipeline Science and Engineering, 2023, (JCR二区)

15.袁子云, 刘刚, 陈雷, 邵伟明, 张钰晗. 融合机制与高斯混合回归算法的成品油管道顺序输送混油长度预测模型. kaiyun体育登录网页入口学报, 2023 (EI)

16.Weiming Shao, Yougao Li, Wenxue Han, et al. Block-Wise Parallel Semisupervised Linear Dynamical System for Massive and Inconsecutive Time-Series Data With Application to Soft Sensing. IEEE Transactions on Instrumentation and Measurement, 2022 (SCI二区TOP)

17.Weiming Shao, Jingbo Wang, Chuanfa Xiao, et al. Real-time estimation of quality-related variable for dynamic and non-Gaussian process based on semisupervised BayesianHMM. Journal of Process Control, 2022 (SCI二区)

18.Ping Wang, Yichao Yin, Wei Bai, Xiaogang Deng, Weiming Shao^*. A unified just-in-time learning paradigm and its application to adaptive soft sensing for nonlinear and time-varying chemical process. Chemical Engineering Science, 2022 (SCI二区TOP)

19.Guoqing Mu, Junghui Chen, Jingxiang Liu, Weiming Shao, et al. State prediction of distributed parameter systems based on multi-source spatiotemporal information, Journal of Process Control, 2022 (SCI二区)

20.Ping Wang, Yichao Yin, Xiaogang Deng, Yingchun Bo, Weiming Shao^*. Semi-supervised echo state network with temporal–spatial graph regularization for dynamic soft sensor modeling of industrial processes, ISA Transactions, 2022 (SCI二区TOP)

21.Weiming Shao, Wenxue Han, Yougao Li, et al. Enhancing the reliability and accuracy of data-driven dynamic soft sensor based on selective dynamic partial least squares models, Control Engineering Practice, 2022 (SCI二区)

22.Weiming Shao, Zhiqiang Ge, Zhihuan Song, Semisupervised Bayesian Gaussian Mixture Models for non-Gaussian Soft sensor, IEEE Transactions on Cybenetrics, 2021 (SCI一区TOP)

23.Jingbo Wang, Weiming Shao^*, Xinmin Zhang, Zhihuan Song*. Dynamic Variational Bayesian Student's T Mixture Regression With Hidden Variables Propagation for Industrial Inferential Sensor Development. IEEE Transactions on Industrial Informatics, 2021 (SCI一区TOP)

24.Le Yao, Weiming Shao, Zhiqiang Ge, Hierarchical Quality Monitoring for Large-Scale Industrial Plants With Big Process Data, IEEE Transactions on Neural Networks and Learning Systems, 2021 (SCI一区TOP)

25.Chihang Wei, Weiming Shao, Zhihuan Song, Virtual sensor development for multi-output nonlinear processes based on bilinear neighborhood preserving regression model with localized construction, IEEE Transactions on Industrial Informatics, 2021 (SCI一区TOP)

26.Jingbo Wang, Weiming Shao^*, Xinmin Zhang, Jinchuan Qian, Zhihuan Song*, Zhiping Peng. Nonlinear variational Bayesian Student’s-t mixture regression and inferential sensor application with semisupervised data. Journal of Process Control, 2021 (SCI二区)

27.Weiming Shao, Zhiqiang Ge, Zhihuan Song, Jingbo Wang, Semi-supervised Robust Modeling of Multimode Industrial Processes for Quality Variable Prediction Based on Student's t Mixture Model, IEEE Transactions on Industrial Informatics, 2020 (SCI一区TOP)

28.Weiming Shao, Zhiqiang Ge, Zhihuan Song, Bayesian Just-in-time learning and its application to industrial soft sensing, IEEE Transactions on Industrial Informatics, 2020 (SCI一区TOP)

29.Weiming Shao, Zhiqiang Ge, Le Yao, et al. Bayesian Nonlinear Gaussian Mixture Regression and its Application to Virtual Sensing for Multimode Industrial Processes, IEEE Transactions on Automation Science and Engineering, 2020 (SCI二区TOP)

30.Kang Liu, Weiming Shao^*, Guoming Chen, Autoencoder-based nonlinear Bayesian locally weighted regression for soft sensor development, ISA Transactions, 2020 (SCI二区TOP)

31.Weiming Shao, Zhiqiang Ge, Zhihuan Song, Parallel Computing and SGD Based DPMM For Soft Sensor Development With Large-Scale Semisupervised Data, IEEE Transactions on Industrial Electronics, 2019 (SCI一区TOP)

32.Weiming Shao, Zhiqiang Ge, Zhihuan Song, Soft-Sensor Development for Processes With Multiple Operating Modes Based on Semisupervised Gaussian Mixture Regression, IEEE Transactions on Control Systems and Technology, 2019 (SCI二区TOP)

33.Weiming Shao, Zhiqiang Ge, Zhihuan Song, Quality Variable Prediction for Chemical Processes Based on Semisupervised Dirichlet Process Mixture of Gaussians, Chemical Engineering Science, 2019 (SCI二区TOP)

34.Weiming Shao, Zhiqiang Ge, Zhihuan Song, Kai Wang, Nonlinear Industrial Soft Sensor Development Based on Semi-supervised Probabilistic Mixture of Extreme Learning Machines, Control Engineering Practice, 2019 (SCI二区)

35.Weiming Shao, Zhiqiang Ge, Zhihuan Song, Semi-supervised Mixture of Latent Factor Analysis Models with Application to Online Key Variable Estimation, Control Engineering Practice, 2019 (SCI二区)

36.Weiming Shao, Hongwei Zhang, Zhihuan Song, Robust supervised probabilistic factor analysis and its application to industrial soft sensor modeling, IEEEAccess, 2019 (SCI二区)

37.Jingbo Wang, Weiming Shao^*, Zhihuan Song*, Robust Inferential Sensor Development Based on Variational Bayesian Student's-t Mixture Regression, Neurocomputing, 2019 (SCI二区TOP)

38.Jingbo Wang, Weiming Shao^*, Zhihuan Song*, Semi-supervised Variational Bayesian Student's t Mixture Regression and Robust Inferential Sensor Application, Control Engineering Practice, 2019 (SCI二区)

39.邵伟明, 葛志强, 李浩, 宋执环. 基于循环神经网络的半监督动态软测量建模方法. 电子测量与仪器学报, 2019 (中文核心)

40.Weiming Shao, Sheng Chen, Chris J. Harris, Adaptive Soft Sensor Development for Multi-Output Industrial Processes Based on Selective Ensemble Learning, IEEE Access, 2018 (SCI二区)

41.Jingbo Wang, Weiming Shao*, Zhihuan Song, Student’s-t Mixture Regression-Based Robust Soft Sensor Development for Multimode Industrial Processes, Sensors, 2018 (SCI三区)

42.邵伟明,田学民,宋执环,基于集成学习的多产品化工过程软测量建模方法, 化工学报, 2018, (EI)

43.Weiming Shao, Xuemin Tian. Semi-supervised selective ensemble learning based on distance to model for nonlinear soft sensor development, Neurocomputing, 2017 (SCI二区TOP)

44.Weiming Shao, Igor Boiko, Ahmed Al-Durra. Plastic bag model of the artificial gas lift system for slug analysis, Journal of Natural Gas Science and Engineering, 2016 (SCI二区)

45.Weiming Shao, Igor Boiko, Ahmed Al-Durra. Control-oriented modeling of gas-lift system and analysis of casing-heading instability, Journal of Natural Gas Science and Engineering, 2016 (SCI二区)

46.Weiming Shao, Xuemin Tian. Adaptive soft sensor for quality prediction of chemical processes based on selective ensemble of local partial least squares models, Chemical Engineering Research and Design, 2015 (SCI二区)

47.Weiming Shao, Xuemin Tian, Ping Wang, Xiaogang Deng, Sheng Chen. Online soft sensor design using local partial least squares models with adaptive process state partition, Chemometrics and Intelligent Laboratory Systems, 2015 (SCI二区)

48.Weiming Shao, Xuemin Tian, Ping Wang. Supervised local and non-local structure preserving projections with application to just-in-time learning for adaptive soft sensor, Chinese Journal of Chemical Engineering, 2015 (SCI四区)

49.Weiming Shao, Xuemin Tian, Ping Wang. Soft sensor development for nonlinear and time-varying processes based on supervised ensemble learning with improved process state partition. Asia-Pacific Journal of Chemical Engineering, 2015 (SCI四区)

50.Weiming Shao, Xuemin Tian, Ping Wang. Local partial least squares based on line soft sensing method for multi-output processes with adaptive process state division, Chinese Journal of Chemical Engineering, 2014 (SCI四区)

51.邵伟明, 田学民. 局部主成分分析及其在软测量中的应用, 自动化仪表, 2014 (中文核心)

52.邵伟明,田学民, 王平, 基于递推PLS核算法的软测量在线学习方法, 化工学报, 2012 (EI)

53.邵伟明, 田学民. 基于快速留一交叉验证法的在线递推最小二乘支持向量机建模方法, 青岛科技大学学报, 2012, (中文核心)

·         ※ 专利

1.邵伟明, 等. 基于混合单隐层神经网络的混油长度在线估计方法及系统, 发明专利, 授权

2.邵伟明, 等. 一种基于鲁棒卡尔曼滤波的潜油机器人定位方法及系统, 发明专利, 授权

3.邵伟明, 等. 一种线性动态系统模型的分布式训练方法, 发明专利, 授权

4.邵伟明, 等, 一种基于半监督混合模型的聚丙烯熔融指数预测方法, 发明专利, 授权

5.邵伟明, 等. 一种基于半监督贝叶斯高斯混合模型的合成氨过程一段炉氧气含量在线估计方法,发明专利, 授权

6.邵伟明, 等. 一种基于鲁棒混合模型的化工过程浓度变量在线估计方法, 发明专利, 授权

7.宋执环, 邵伟明, 等, 基于半监督非线性变分贝叶斯混合模型的成分参数鲁棒软测量方法, 发明专利, 授权

8.袁子云, 陈雷, 邵伟明, 等, 机理-数据双驱动的成品油管道混油长度预测方法及系统, 发明专利, 授权

9.陈雷, 袁子云,邵伟明, 等, 基于历史数据的成品油管道混油浓度分布预测方法及系统, 发明专利, 授权