特别副研究员

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王典朋

个人简介


Personal Information

Name:  Dianpeng Wang (王典朋)

Born:  October 17, 1984, Yuncheng, ShanXi, China

Email:  wdp@bit.edu.cn 

Institute:  School of Mathematics and Statistics, BIT, 100081, China

Address: No.5 Zhongguancun South Street, Haidian District, Beijing, China


Educational Background

► 09/2012--06/2016, PhD in Statistics, Beijing Institute of Technology. Supervisor: Prof. Yubin Tian. Major: Experimental Design

09/2008—06/2010, Master in Statistics, Beijing Institute of Technology. Supervisor: Prof. Yubin Tian. Major: Experimental Design

► 09/2003--07/2007, Bachelor in StatisticsBeijing Institute of Technology.


Working Experience

► 05/2018--Present, Assistant Professor, School of Mathematics and Statistics, Beijing Institute of Technology.

► 07/2016—05/2018, Posdoctor, Academy of Mathematics and Systems Science, Chinese Academy of Sciences. Supervisor: Prof. Dan Yu.

► 09/2011—09/2012, Algorithm Engineer, Alpine data Labs.

► 07/2010—08/2012, Data Analyst, Hua Yuan data analysis co. LTD.

► 07/2007—08/2008, Teaching Assistant, Mathematics experiment center of BIT.


Publications

1. Wang, D. P. and Tian, Y. B. (2014). “An Adaptive Design to Assess the Reliability of the Pyrotechnic Control Subsystem in Opening the Solar Array”. Acta Mathematica Application Sinica (English Series), 30, 1037—1048.

2. Wang, D. P., Tian, Y. B. and Xu, Y. (2015). “An Optimal Stochastic Approximation for Estimating the Effective Window of a Control Factor”. Journal of Systems Science and Complexity, 28, 1258—1270.

3. Wang, D. P., Tian, Y. B. and Wu, C. F. Jeff. (2015). “A Skewed version of Robbins-Monro-Joseph Procedure for Binary Response”. Statistica Sinica, 25, 1679—1689.

4. Ba, S., Myers, W. R. and Wang, D. P. (2018). “A Sequential Maximum Projection Design Framework for Computer Experiments with Inert Factors”. Statistica Sinica, 28: 879-897.

5. Wang, D. P., Tian, Y. B. and Wu, C. F. Jeff. (2020) “Comprehensive Comparisons of Major Procedures for Sensitivity Testing”. Journal of Quality Technology, 52(2): 155-167.

6. Joseph, R. V., Wang, D. P., Li, G., Lv, S. J. and Tuo, R.(2019). “Deterministic Sampling of Expensive Posteriors Using Minimum Energy Designs”. Technometrics, 61(3): 297-308.

7. Li Jialu#; Tian Yubin#; Wang Dianpeng* (2020). Change-point detection of failure mechanism for electronic devices based on Arrhenius model, Applied Mathematical Modelling, 2020, 83: 46-58. 


Visiting Positions

► 06/2019—2/2020, Visiting Scholar, Industrial Engineering & Decision Analytics, Hong Kong University of Science and Technology. Supervisor: Prof. Fugee Tsung.

► 08/2013—12/2015, Visiting Scholar, School of Industrial & Systems Engineering, Georgia Institute of Technology. Supervisor: Prof. C. F. Jeff Wu.


Awards, Honors and Recognitions

► 2017, Zhong JiaQing Awards, Chinese society of mathematical statistics.


Conference Talks and Invited Presentations

1. Wang, D. P. (2014). “A skewed version of Robbins-Monro-Joseph procedure for Binary Response”, Joint Statistical Meeting.

2. Wang, D. P. (2015). “Comprehensive Comparisons of Major procedure for Sensitivity Testing”, Spring Research Conference on Statistics in Industry and Technology.

3. Wang, D. P. (2016). “Bayesian Computation Using Minimum Energy Designs”. 2016 National Experiment Design and Application Conference. Qufu Normal University, ShanDong, China.

4. Wang, D. P. (2017). “A Sequential Maximum Projection Design Framework for Computer Experiments with Inert Factors”. 2017 National Experiment Design and Application Conference. LanZhou University of Finance and Economics, GanSu, China.

5. Wang, D. P. (2018). “Efficient Sequential Experimental Design for Estimating Therapeutic Window”. 2018 National Experiment Design Conference and Statistical Seminar. Beijing Institute of Technology, Beijing, Beijing.

6. Yubin Tian; Wang Dianpeng (2020); Adaptive Bayesian Prediction of Reliability Based on Degradation Process, Statistics And Innovation For Industry 4.0,  ItalyFlorence.


Fundings

► 01/2019--12/2021, National Natural Science Foundation of China (NSFC) (Grant No. 11801034), Principal Investigator

► 01/2019--01/2020, China Postdoctoral Science Foundation funded project (Grant No. 2016M601149), Principal Investigator


Interests

Experimental Design; Bayesian Computation; Uncertainty Quantification; Industrial Big Data