西安交通大学人居环境与建筑工程学院导师教师师资介绍简介-赵腾远

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Welcome - 赵腾远基本信息

赵腾远
博士，特聘研究员，博导
2019年入选西安交大青年拔尖计划
课题组常年招聘具有岩土工程、
地质工程、计算机科学、
地理信息、机器学习背景的硕士、
博士、博士后、交流访问****等，
诚邀有志于从事岩土工程、地质工程
与机器学习交叉研究的学生****加盟
或交流探讨。欢迎来信联系。

工作经历
2019.08-至今，西安交通大学，特聘研究员
2017.09-2019.08，中国香港城市大学，博士后研究助理

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研究领域
贝叶斯岩土场地的概率勘察
基于机器学习的岩土空间变异性刻画
地质灾害智能监测
岩土结构可靠度分析与设计
空间数据（Spatial data）分析与仿真

联系方式
院系：土木工程系，人居环境与建筑工程学院
地址：陕西省西咸新区西安交通大学西部科技创新港，19号楼，办公室3085
Email：tyzhao@xjtu.edu.cn

基金项目
主持轨道交通工程信息化国家重点实验室（中铁一院）开放基金：基于信息熵及图像处理的黄干裂缝智能预测与识别，2020.01-2021.06
主持西安交通大学学科交叉与合作课题：基于多光谱遥感图像和机器学习的黄土滑坡智能识别，2020.01-2022.12

教育经历
2014.08-2017.08，中国香港城市大学，岩土工程专业，博士
2011.09-2014.06，西南交通大学，地质工程专业，硕士
2007.09-2011.06，西南交通大学，地质工程专业，学士

科研成果 - 赵腾远科研论文
Zhao, T.*, Lei, Jieyang, Xu, Ling (2021). “An efficient Bayesian method for estimating runout distance of region-specific landslides using sparse data.” Georisk, in press. (SCI, IF2019 = 4.811)
Zhao, T*., Wang, Y., and Xu, L. (2021). “Efficient CPT locations for characterizing spatial variability of soil properties within a multilayer vertical cross-section using information entropy and Bayesian compressive sensing.” Computers and Geotechnics, 137, 104260.(SCI, IF2019 = 3.818, JCR Q1)
Guan, Z., Wang, Y*., and Zhao, T. (2021). “Delineating the spatial distribution of soil liquefaction potential in a cross-section from limited cone penetration tests.” Soil Dynamics and Earthquake Engineering, 145, 106710. (SCI, IF2019 = 2.637 , JCR Q1)
Zhao, T., Wang, Y*.(2021). "Statistical Interpolation of Spatially Varying but Sparsely Measured 3D Geo-Data Using Compressive Sensing and Variational Bayesian Inference." Math Geosci (2021). https://doi.org/10.1007/s11004-020-09913-x
Xu, L., Yan, D., andZhao, T*. (2021). “Probabilistic evaluation of loess landslide impact using multivariate model.”Landslides, 18,1011–1023, https://doi.org/10.1007/s10346-020-01521-4. (SCI, IF2019 =4.252, JCRQ1)
Zhao, T., and Wang, Y*. (2020). “Non-parametric simulation of non-stationary non-Gaussian 3D random field samples directly from sparse measurements using signal decomposition and Markov Chain Monte Carlo.”Reliability Engineering & System Safety, 203, 107087. (SCI,IF2019=5.040, JCR Q1)
Zhao, T., Xu, L., and Wang, Y*. (2020). “Fast non-parametric simulation of 2D non-stationary cone penetration test (CPT) data without pre-stratification using Markov Chain Monte Carlo simulation.”Engineering Geology, 273, 105670. (SCI,IF2019=4.779, JCRQ1)
Zhao, T., and Wang, Y*. (2020). “Differentiation of discrete data with unequal measurement intervals and quantification of uncertainty in differentiation using Bayesian compressive sampling.”Computers and Geotechnics, 122, 103537. (SCI,IF2019=3.818, JCRQ1)
Zhao, T., Wang Y*. (2020) “Interpolation and stratification of multilayer soil property profile from sparse measurements using machine learning methods.”Engineering Geology,265,105430. (SCI,IF2019=4.779, JCRQ1)
Zhao, T., Wang, Y*. (2019). “Determination of efficient sampling locations in geotechnical site characterization using information entropy and Bayesian compressive sampling.”Canadian Geotechnical Journal,56(11): 1622-1637. (SCI,IF2019=2.802, JCRQ2)
Wang, Y*., Hu, Y., andZhao,T.(2020). “CPT-based subsurface soil classification and zonation in a 2D vertical cross-section using Bayesian compressive sampling.”Canadian Geotechnical Journal,57(7): 947-958. (SCI,IF2019=2.802, JCRQ2)
Hu, Y., Wang, Y*.,Zhao, T.,and Phoon, K.K. (2020) “Bayesian supervised learning of site-specific geotechnical spatial variability from sparse measurements.”Journal of Risk and Uncertainty in Engineering Systems,Part A: Civil Engineering, 6(2), **. (SCI,IF2019=1.331, JCRQ3)
Hu, Y.,Zhao, T., Wang, Y*., Choi, C., and Ng, C. W. W. (2019). “Direct simulation of two-dimensional isotropic or anisotropic random field from sparse measurement using Bayesian compressive sampling.”Stochastic Environmental Research and Risk Assessment, 33, 8-9, 1477–1496. (SCI,IF2019=2.351, JCRQ2)
Montoya-Noguera, S.,Zhao, T., Hu, Y., Wang, Y*., and Phoon, K.K. (2019). “Simulation of non-stationary non-Gaussian random fields from sparse measurements using Bayesian compressive sampling and Karhunen-Loève expansion.”Structural Safety,79, 66-79. (SCI,IF2019=4.522, JCRQ1)
Wang, Y*.,Zhao, T., Phoon, K.K (2019). “Statistical inference of random field auto-correlation structure from multiple sets of incomplete and sparse measurements using Bayesian compressive sampling-based bootstrapping”.Mechanical Systems and Signal Processing,124, 217-236. (SCI,IF2019=6.471,Q1)
Zhao, T., Hu, Y. and Wang, Y*. (2018). “Statistical interpretation of spatially varying 2D data from sparse measurements using Bayesian compressive sampling.”Engineering Geology,246: 162-175. (SCI,IF2019=4.779, JCRQ1)
Zhao, T.*and Wang, Y. (2018). “Interpretation of pile lateral response from deflection measurement data: a compressive sampling-based method.”Soils and Foundations,54(8), 957-971. (SCI,IF2019=1.756, JCRQ3)
Zhao, T.and Wang, Y*. (2018). “Simulation of cross-correlated random field samples from sparse measurements using Bayesian compressive sensing.”Mechanical Systems and Signal Processing, 112, 384-400. (SCI,IF2019=6.471, JCRQ1)
Zhao, T., Montoya-Noguera, S., Phoon, K.K. & Wang, Y*(2018). “Interpolating spatially varying soil property values from sparse data for facilitating characteristic value selection.”Canadian Geotechnical Journal, 55(2), 171-181. (SCI,IF2019=2.802, JCRQ2)
Wang, Y*.,Zhao, T., Hu, Y. and Phoon, K.K. (2018). “Simulation of random fields with trend from sparse measurements without de-trending.”Journal of Engineering Mechanics(ASCE),145(2), **. (SCI,IF2019=2.003, JCRQ2)
Wang, Y*., Guan, Z. andZhao, T.(2018). “Sample size determination in geotechnical site investigation considering spatial correlation.”Canadian Geotechnical Journal,56(7), 992-1002. (SCI,IF2019=2.802, JCRQ2)
Wang, Y*.,Zhao, T.and Phoon, K.K. (2018). “Direct simulation of random field samples from sparsely measured geotechnical data with consideration of uncertainty in interpretation.”Canadian Geotechnical Journal, 55(6), 862-880. (SCI,IF2019=2.802, JCRQ2)
Wang, Y*., Akeju, O.V. andZhao, T.(2017). “Interpolation of spatially varying but sparsely measured geo-data: a comparative study.”Engineering Geology, 231, 200-217. (SCI,IF2019=4.779, JCRQ1)
Wang, Y*. andZhao, T.(2017). “Bayesian assessment of site-specific performance of geotechnical design charts with unknown model uncertainty.”International Journal for Numerical and Analytical Methods in Geomechanics, 41(5), 781-800. (SCI,IF2019=2. 814, JCRQ2)
Wang, Y*. andZhao, T.(2017). “Statistical interpretation of soil property profiles from sparse data using Bayesian compressive sampling.”Géotechnique, 67(6), 523-536. (SCI,IF2019=3.830, JCRQ1)
Wang, Y*. andZhao, T.(2016). “Interpretation of soil property profile from limited measurement data: a compressive sampling perspective.”Canadian Geotechnical Journal, 53(9), 1547-1559. (SCI,IF2019=2.814, JCRQ2)
Wang, Y*.,Zhao, T., and Cao, Z. (2015). “Site-specific probability distribution of geotechnical properties.”Computers and Geotechnics, 70, 159-168. (SCI,IF2019=3.818, JCRQ1)
赵腾远, ALADEJARE Adeyemi Emman &王宇. (2016). “基于贝叶斯方法的模型选择以及岩石性质概率表征”.武汉大学学报(工学版)第5期: 740-744.
曹子君,赵腾远,王宇, &王鹰. (2015). “基于贝叶斯等效样本的土体杨氏模量的统计特征确定方法”.防灾减灾工程学报第5期: 581-585.

Awards - 赵腾远 The 2020 Best Paper Award, the ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering: Hu, Y., Wang, Y., Zhao, T., and Phoon, K. K. (2020). "Bayesian supervised learning of site-specific geotechnical spatial variability from sparse measurements." ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 6(2), **.
Canadian Geotechnical Journal "Editor’s choice" Paper: Zhao, T. and Wang, Y. (2019). “Determination of efficient sampling locations in geotechnical site characterization using information entropy and Bayesian compressive sampling.” Canadian Geotechnical Journal, 56(11), 1622-1637.