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石茂林
发布日期:2022-06-14   浏览次数:
姓  名 石茂林出生年月 1990.04

政治面貌 群众最高学位 工学博士
职  称 助理研究员
(资格副研究员)
任职年月 2020.09
职  务 任职年月
所在学科  博导/硕导
学习与工作经历

学习经历:
2008.09-2012.06 重庆大学 机械电子工程       导师:廖强
2008.09-2012.06 重庆大学 工商管理(二专)   导师:李奔波
2012.09-2015.06 华侨大学 机械制造及其自动化 导师:李洪友
2015.09-2020.07 大连理工大学 机械设计及理论 导师:孙伟/宋学官(******)
工作经历:
2020.09-至今 江苏大学 助理研究员(资格副研究员)

学术与社会任职  
主讲课程

本科生
数字信号处理

研究领域

数据建模及其驱动的预测技术

科研项目

在研项目
1.江苏省青年基金项目
2.博士后面上基金项目
3.省部共建现代农业装备与技术协同创新中心项目
4.江苏大学高级人才引进项目
5.江苏省农业自主创新基金(学校任务负责人)
结题项目

主要论著

论文
一、以第一作者或第二作者(导师一作)发表SCI论文8篇(单篇三年内最高引用38次),国际会议最佳论文奖1篇。
1. Shi M., Sun W., Song X.*, Zhang L. A fuzzy c-means algorithm guided by attribute correlations and its application in the big data analysis of tunnel boring machine. Knowledge-based Systems. 2019.
2. Shi, M., Zhang, T., Zhang, L., Sun, W., Song, X*. A fuzzy c-means algorithm based on the relationship among attributes of data and its application in tunnel boring machine. Knowledge-Based Systems, 191(2020), 105229.
3. Shi, M., Lv, L., Song, X.*, & Sun, W. A support vector regression-based multi-fidelity surrogate model. Structural and Multidisciplinary Optimization, (2020).
4. Shi, M.*, Li, H., Liu, X. Multidisciplinary design optimization of dental implant based on finite element method and surrogate models. Journal of Mechanical Science & Technology, 31(2017), 5067-5073.
5. Sun, W.(导师), Shi, M., Zhang, C., Zhao, J., Song, X*. Dynamic load prediction of tunnel boring machine (TBM) based on heterogeneous in-situ data. Automation in Construction. 92(2018), 23-34.
6. Sun, W.(导师), Shi, M., Li, J., Ding, X., Wang, L., Song, X*. Surrogate-Based Multisource Sensitivity Analysis of TBM Driving System. Shock and Vibration, 2018.
7. Song X.(导师), Shi M.*, Sun W. A new fuzzy c-means clustering-based time series segmentation approach and its application on tunnel boring machine analysis. Mechanical Systems and Signal Processing. 133(2019):106279
8. Li, H.(导师), Shi M.*, Liu X., Shi Y. Uncertainty optimization of dental implant based on finite element method, global sensitivity analysis and support vector regression. Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine (2018): 0954411918819116.
9. Shi M., Wang X., Sun W., Song X*. Optimization of Material and Structure Parameters in Dental Implant, QR2MSE2016& WCEAM. (2016) (Best paper reward).
10. Shi, M., Sun W., Zhang T., Liu Y., Wang S. & Song X*. Geology prediction based on operation data of TBM: comparison between deep neural network and soft computing methods. 2019 1st International Conference on Industrial Artificial Intelligence (2019).
二、合作发表SCI论文如下:
1. Lv, L., Shi, M., Song, X.*, Sun, W., & Zhang, J. A Fast-Converging Ensemble Infilling Approach Balancing Global Exploration and Local Exploitation: The Go-Inspired Hybrid Infilling Strategy. Journal of Mechanical Design, (2019):1-27.
2. Gao X., Shi M., Song X., Zhang C.*, Zhang, H. Recurrent neural networks for real-time prediction of TBM operating parameters. Automation in Construction, 98(2019): 225-235.
3. Zhao, J., Shi, M., Hu, G., Song, X., Zhang, C.*, Tao, D., & Wu, W. A Data-Driven Framework for Tunnel Geological-Type Prediction Based on TBM Operating Data. IEEE Access. (2019). (IF:4.098).
4. Sun, W., Wang, X., Shi, M.*, Wang, Z., Song, X. Multidisciplinary design optimization of hard rock tunnel boring machine using collaborative optimization. Advances in Mechanical Engineering, 10(2018), 1687814018754726.
5. Fang, J., Song, X., Yao, N., & Shi, M*. Application of FCM Algorithm Combined with Artificial Neural Network in TBM Operation Data. Computer Modeling in Engineering & Sciences, 126(2021), 397-417.

获奖情况

国家奖学金,QR2MSE国际会议最佳论文奖。

发明专利  
重要学术活动

学术报告:
1.“A fuzzy c-means algorithm guided by attribute correlations for the In-situ Data Clustering of Tunnel Boring Machine”, 清华大学, 2017.
2. “Data Clustering and Time Series Segmentation for Complex Engineering Systems”, 第11届中国R会议,中国人民大学, 2018.
3.“数据挖掘技术在重大装备中的应用”, 西安电子科技大学, 2019.

人生格言  
联系方式

maolin@ujs.edu.cn(欢迎对机器学习、数据挖掘感兴趣的同学前来探讨!)

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