个人简介
中国现场统计研究会试验设计分会副理事长,中国数学会均匀设计分会副主任委员,长期从事数理统计、试验设计与可靠性优化方向的研究;多次在全国和国际学术会议做大会报告和邀请报告,作为国际会议主席(共同)主持国际会议3次。 先后主持国家自然科学基金委项目、国家国防科技工业局技术基础项目和航天预先研究项目、原总装备部共性技术预先研究项目和重点基金项目10余项。研究成果已经应用于我国十余种燃爆产品的可靠性设计与分析、以及天宫系列卫星和我国新一代遥感卫星智能系统的设计与研发。获国防科技进步奖2项、军队科技进步奖1项。研究成果被编制为国军标1项,美军标1项。
教育背景
1983.09-1987.06,北京师范大学数学学科,本科
1987.09-1990.06,北京师范大学数学学科,硕士
1996.03-2000.03,北京理工大学兵器科学与技术学科,博士
工作经历
2000.10-2022.09,中国科学院数学与系统科学研究院,博士后
2004.09-2005.08,美国佐治亚理工大学工业与系统工程学院,访问学者
1990.06-,北京理工大学数学和统计学科教师
近期论文
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V. Roshan Joseph, Yubin Tian and C. F. Jeff Wu. Adaptive designs for stochastic root-finding. Statistica Sinica, 2007, 17(4):1549-1565.
Yubin Tian. Consistency of the maximum likelihood estimator and Bayesian estimator based on sequential sensitivity experiments. Statistics and Probability Letters, 2009, 79(6):728–732.
C.F. Jeff Wu, Yubin Tian ; Three-phase optimal design of sensitivity experiments. Journal of Statistics Planning and Inference, 2014, 149:1-15.
Dianpeng Wang, Yubin Tian , C.F. Jeff Wu. A skewed version of the Robbins-Monro-Joseph procedure for binary response. Statistica Sinica, 2015, 25(4): 1679-1689.
Xia Cai,Yubin Tian, Wei Ning. Modified information approach for detecting change points in piecewise linear failure rate function. Statistics & Probability Letters, 2017, 125: 130-140.
Xia Cai, Yubin Tian, Wei Ning. Change-point analysis of the failure Mechanisms based on accelerated life tests. Reliability Engineering & System Safety, 2019, 188: 515-522.
Dianpeng Wang, Yubin Tian , C.F. Jeff Wu. Comprehensive comparisons of major design procedure for sensitivity testing. Journal of Quality Technology, 2020, 52(2): 155-167.
Jialu Li, Yubin Tian, Dianpeng Wang. Change-point detection of the failure mechanism for electronic devices based on Arrhenius model. Applied Mathematical Modelling, 2020, 83: 46-58.
Yongfei Fang, Yubin Tian, Xia Cai. Sequential designs for estimating the operating window. Communications in Statistics-Simulation and Computation, 2021(8): 2386-2398.
Jun Wang, Dianpeng Wang, Yubin Tian. Multidimensional specification test based on non-stationary time series. TEST, 2022, 31: 348-372.