• 日期:March 22, 2018    作者:    阅读:    字体:/ 大    小 /

工作经历


2015.9 至今:必赢nn699net 副教授

教育经历


2007.9—2011.7:南开大学数学科学学院统计系 学士

2011.9—2015.7:香港科技大学工业工程及物流管理学系 博士

学术成果


论文:

1) Bai, K., Li, J. and Ding, D., 2023. Two approaches to monitoring multivariate Poisson counts: Simple and accurate. IISE Transactions.

2) Li, J., Ding, D., and Tsung, F., 2022. Directional PCA for Fast Detection and Accurate Diagnosis: A Unified Framework. IEEE Transactions on Cybernetics, 52 (11), 11362-11372.

3) Xiang, D., Pu, X., Ding, D. and Liang, W., 2021. An Efficient Charting Scheme for Multivariate Categorical Process with a Sparse Contingency Table. Journal of Quality Technology, 53(1), 88-105.

4) Ding, D. and Li, J., 2020. Efficient Monitoring of Overdispersed Counts with Time-Varying Population Sizes. Computers and Industrial Engineering, 143, 106409.

5) Li, J., Zhou, Q., and Ding, D., 2020. Efficient Monitoring of Autocorrelated Poisson Counts. IISE Transactions, 52(7), 769-779.

6) Wang, J., Ding, D., Su, Q., 2019. Latent Change-point Detection in Ordinal Categorical Data, Quality and Reliability Engineering International, 35(2), 504-516.

7) Ding, D., Xiang, D., and Li, J., 2017. Directional Monitoring of Categorical Processes with Serial Dependence, Computers & Industrial Engineering, 113, 502-511. 

8) Ding, D., Tsung, F., and Li, J., , 2017. Ordinal Profile Monitoring with Random Explanatory Variables. International Journal of Production Research, 55(3), 736-749. 

9) Ding, D., Tsung, F., and Li, J., , 2016. Rank-based Process Control for Mixed-Type Data. IIE Transactions, 48(7), 673-683. (IISE Magazine feature article) 

10) Ding, D., Tsung, F., and Li, J., 2016. Directional Control Schemes for Processes with Mixed-type Data. International Journal of Production Research, 54(6), 1594-1609.

11) 李阳, 丁冬*, 2020. 基于拟合优度检验的非参数 EWMA 控制图, 系统科学与数学, 40(5), 917-926.

专著:

李健, 丁冬:《分类数据的统计过程控制》, ISBN:978-7-03-065121-1, 科学出版社, 北京, 2021.

科研项目


主持:

1) 陕西省教育厅重点科学研究计划项目,21JZ03,纺织过程中复杂数据的质量控制研究,2021.01-2023.12

2) 国家自然科学基金青年项目,71602155,多模式形状轮廓的统计质量控制,2017.01-2019.12

参与:

1) 国家自然科学基金面上项目,72271193,复杂轮廓数据的质量监控研究:基于分位数的视角,2023.01-2026.12

2) 国家自然科学基金面上项目,71772147,复杂高维数据流的实时监控策略研究,2018.01-2021.12

奖励荣誉


1) IISE (formerly Industrial Engineer) Magazine feature article, 2016

2) 香港桑麻奖教金,2018年

联系方式


Email: laceyding@foxmail.com


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