副教授 统计与数据科学系

蒋学军,副教授。2009年获香港中文大学统计学博士学位, 09年09月-10年10月在香港中文大学统计学系从事博士后研究,10年7月-13年6历任中南财经政法大学统计与数学学院讲师、副教授、研究生导师。13年07月加入南方科技大学,获国家自然科学基金(青年,面上)、广东省自然科学基金(2项)、深圳市科创委项目、深圳市技术委托开发项目、广东省本科高校金融学类教改项目等。主要科研方向为数理统计、金融统计与计量,已发表SCI&SSCI期刊论文近40篇。

个人简介

工作经历:

2019.07-present,  副教授,统计与数据科学系, 南方科技大学

2015.07-2019.06, Tenure-Track助理教授,数学系,南方科技大学

2013.07-2015.06, Tenure-Track助理教授,金融数学与金融工程系,南方科技大学

2011.09-2014.01, 班主任&指导教师,中南财经政法大学,2011级EMBA深圳班

2011.10-2013.07 副教授&教研室主任, 硕士生导师,数理统计与金融统计系,中南财经政法大学

2010.10-2011.09 讲师,数学与数量经济系,中南财经政法大学

2009.09-2010.09 博士后,香港中文大学统计学系

 

教育背景:

博士,香港中文大学,香港, 2009

硕士,云南大学,昆明, 2006

本科,国防科技大学,长沙, 2000

 

所获荣誉:

○ 深圳市优秀教师,2018

○ 南方科技大学 “杰出教学奖”,2018

○ 南方科技大学 “优秀导师奖”,2016

○ 深圳市海外高层次人才“孔雀计划”入选者

 

 

研究领域

· 分位数回归

· 参数和非参数推断

· 高维数据降维与分析

· 金融与计量经济统计

· 贝叶斯分析及应用


教学

Multivariate Statistics Analysis (2018 Spring)

Econometrics (2018 Spring)

Time Series Analysis (2018 Fall)

Advanced Statistics (2018 Fall, postgraudates)


学术成果 查看更多

· Tan, F., Jiang. X., Guo, X. and Zhu, L. (2019). Testing heteroscedasticity for regression models based on projections. Statistica Sinica, online.

· Guo, X., Jiang. X., Zhang, S. and Zhu, L. (2019). Pairwise distance-based heteroscedasticity for regressions. Science China- Mathematics, online.

· Jiang, X., Fu, Y., Jiang, J., Li, J. (2019). Spatial Distribution of the Earthquake in Mainland China. Physica A: Staitsical Mechanics and its Application, online.

· Jiang, X., Li, Y. , Yang, A. and Zhou, R. (2018). Bayesian semiparametric quantile regression modeling for estimating earthquake fatality risk. Empirical Economics, online.

· Lin, H., Jiang, X., Liang, H. and Zhang, W. (2018). Reduced rank modelling for functional regression with functional responses. Journal of multivariate analysis,169,205-217.

· Jiang, X. and Fu, Y. (2018). Measuring the Benefits of Development Strategy of “The 21st CenturyMaritime Silk Road” via Intervention Analysis Approach: Evidence from China and Neighboring Countries in Southeast Asian. Panoeconomicus,65(5)

· Xia, T., Jiang, J. and Jiang, X. (2018). Local influence for quasi-likelhood nonlinear models with random effects. Journal of Probability and Statistics. Vol 2018. 7.

· Li, J., Jiang, J., Jiang, X. and Liu, L.(2018). Risk-adjusted Monitoring of Surgical Performance. PLOSONE, 13(8), 1-13

· Zhao, W., Jiang, X. and Liang H. (2018). A Principal Varying-Coefficient Model for Quantile Regression: Joint Variable Selection and Dimension Reduction. Computational Statistics and Data Analysis,127, 269-280. (2018,11)

· Yang, A., Jiang, X., Shu, L., Lin, J. (2018). Sparse Bayesian Kernel Multinomial Probit Regression Model for High-dimensional Data Classification. Communication in statistics-theory and methods. Online

· Tian, G., Liu, Y., Tang, M. and Jiang, X. (2018). Type I multivariate zero-truncated/adjusted distributions with applications. Journal of computational and applied mathematics,344(15), 132-153.

· Jiang X., Guo, X., Zhang, N., Wang, B. and Zhang, B.* (2018). Robust multivariate nonparametric tests for detection of two- sample location shift in clinical trials. PLOSONE,13(4), 1-20.

· Yan A., Liang H., Jiang X. and Liu P. (2018). Sparse Bayesian variable selection for classifying high-dimensional data. Statistics and its interface,11(2), 385-395.

· Tian, G., Zhang, C. and Jiang, X. (2018). Valid statistical inference methods for a case-control study with missing data. Statistical Methods in Medical Research,27(4), 1001-1023.

· Xia T., Jiang X. and Wang X. (2018). Asymptotic properties of approximate maximum quasi-likelihood estimator in quasi- likelihood nonlinear models with random effects. Communication in Statistics,47, 1-12.

· Song, X. Kang, K. Ouyang, M., Jiang, X. and Cai. J. (2018). Bayesian Analysis of Semiparametric Hidden Markov Models with Latent Variables. Structural Equation Modeling: A Multidisciplinary Journal.25(1), 1-20.

· Li J., Liang, H., Jiang, X. and Song, X. (2018). Estimation and Testing for Time-varying Quantile Single-index Models with Longitudinal Data. Computational Statistics and Data Analysis,118, 66-83.

· Feng, K. and Jiang, X. (2017). Variational approach to shape derivatives for elasto-acousticcoupled scattering fields and an application with random interfaces. Journal of Mathematical Analysis and Application,456, 686-704.

· Jiang, J., Jiang. X., Li, J. Li, Y and Yan, W. (2017). Spatial Quantile Estimation of Multivariate Threshold Time Series Models. Physical A: Statistical Mechanics and Its Application,486,772-781.

· Guo, X., Jiang, X. and Wong, W. (2017). Stochastic Dominance and Omega Ratio: Measures to Examine Market Efficiency and Anomaly. Economies, 5(38),1-16.

· Tian, X., Jiang, X., and Wang, X. (2017). Diagnostics for quasi-likelihood nonliear models. Communication in Statistics-Theory and Methods,47(16), 8836-8851.

· Jiang, X., Tian, X. and Wang, X. (2017). Asymptotic properties of maximum quasi-likelihood estimator in quasi-likelihood nonlinear models with stochastic regression. Communication in Statistics-Theory and Methods,46(13), 6229-6239. 22.

· Niu, C. and Jiang, X. (2017). Statistical inference for a novel health inequality index. Theoretical Economics Letters,7, 251-262.

· Yang, A, Jiang, X., Xiang, L and Lin J. (2017). Sparse Bayesian Variable Selection in Multinomial Probit Regression Model with Application to High-dimensional Data Classification. Communication in Statistics-Theory and Methods.46(12), 6137-6150.

· Yang, A., Jiang, X., Shu, L. and Lin J. (2017). Bayesian Variable Selection with Sparse and Correlation Priors for High-dimensional Data Analysis. Computational Statistics,32, 127-143 .

· Huang, X., TIAN, G., Zhang, C. and Jiang, X. (2017). Type I multivariate zero-inflated generalized Poisson distribution with applications. Statistics and Its Interface,10(2), 291-311.

· Yang, A., Jiang, X., Liu, P. and Lin J. (2016). Sparse bayesian multinomial probit regression model with correlation prior for High-dimensional data Classification. Statistics and probability letters,119,241-247.

· Jiang, X., Li, J., Xia, T and Wang, Y. (2016) Robust and efficient estimation with weighted composite quantile regression. Physical A: Statistical Mechanics and its Applications,457, 413-423.

· Jiang, X., Song, X. and Xiong, Z. (2016) Robust and efficient estimation of GARCH models. Journal of Testing and Evaluation,44(5), 1-23.

· Li, H., Tian, G., Jiang, X. and Tang, N. (2016). Testing hypothesis for a simple ordering in incomplete contingency tables. Computational Statistics and Data Analysis,99,25-37.

· Li, Y., Tang, N. and Jiang, X. (2016). Bayesian Approaches for Analyzing Earthquake Catastrophic Risk. Insurance: Mathematics and Economics, 68, 110-119.

· Xia, T., Jiang, X. and Wang, X. (2015). Strong consistency of the maximum quasi-likelihood estimator in quasi-likelihood nonlinear models with stochastic regression. Statistics & Probability letters,103, 37-45

· Xia, T., Wang, X. and Jiang, X. (2014). Asymptotic properties of maximum quasi-likelihood estimator in quasilikelihood nonlinear models with misspecified variance function. Statistics,48(4), 778-786.

· Song, X., Cai, J., Feng, X. and Jiang, X. (2014). Bayesian Analysis of Functional-Coefficient Autoregressive Heteroscedastic Model. Baysian Analaysis,9(2), P1-26.[PDF]

· Jiang, X., Tian, T. and Xie, D. (2014). Weighted type of quantile regression and its application. IMECS2014, II, 818-822.

· Jiang J, Jiang, X. and Song X(2014) Weighted composite quantile regression estimation of DTARCH models.The Econometrics Journal, 17(1),1-23 [PDF]

· Jiang, X., Jiang, J. and Song, X. (2012.). Oracle model selection for nonlinear models based on weighted composite nonlinear quantile regression. Statistica Sinica,22(4), 1479-1506.[PDF]

· Jiang, J. and Jiang, X. (2011). Inference for partly linear additive COX models. Statistica Sinica,21(2),901-921.[PDF]

· Jiang, X., Jiang, J. and Liu, Y. (2011). Nonparameteric regression under double-sampling designs. Journal of Systems Science and Complexity,24, 1-9.

· Xia, T., Wang, X. and Jiang, X. (2010). Asymptotic properties of the MLE in nonlinear reproductive dispersion models with stochastic regressors. Communication in Statistics,Theory and Methods,39, 2800-2810.

· Jiang, J., Marron, J.S. and Jiang, X.(2009). Robust Centroid Quantile Based Classification for High Dimension Low Sample Size Data. Journal of Statistical Planning and Inference,139(8), 2571-2580.

· Jiang, J., Zhou, H.,Jiang, X. and Peng, J. (2007). Generalized likelihood ratio tests for the structures of semiparametric additive models. TheCanadian Journal of Statistics,35(3), 381-398.

在审论文(Revision):

· Jiang J. and Jiang X.* (2019). Nonparametric Inference for Partly Linear Additive Cox Models based on Polynomial Spline Estimation. Journal of the Americal Statistical Association, revision.[PDF]

新闻动态 更多新闻

  • 我校统计与数据科学系正式成立

    2019-08-21
  • 杰出教学奖获得者蒋学军:在南科大任教是一生无悔的选择

    2018-10-11
  • 统计系教师蒋学军获深圳市教育发展基金会表彰

    2018-09-20

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南方科技大学统计与数据科学系蒋学军教授招聘博士后岗位

 

教师简介

蒋学军副教授,南方科技大学统计与数据科学系,博士生导师。

2009年于香港中文大学获得博士学位,09-10(2009/09-2010/09)在港中文从事博士后研究工作,2013年07月加入南方科技大学,入选深圳市海外高层次人才孔雀计划,市优秀教师,主持有国家自然科学基金(青年,面上)、广东省自然科学基金(2项)、深圳市科创委项目、深圳市技术委托开发项目、广东省教学改革项目等。

主要研究方向包括金融统计与计量、分位数回归、变量选择、高维统计推断、及贝叶斯应用等。已在统计学主流期刊和相关金融、经济等交叉学科期刊上发表SCI&SSCI论文40余篇,并出版专著一部。

课题组依托南方科技大学统计与数据科学系,配备高性能计算平台,提供优厚的薪酬待遇,欢迎各位充满学术热情的青年才俊加盟。我们将打造自由灵活的学术研究环境、良好的实验平台和国际化的研究视野与科研团队。

 

 

 

招聘信息

(一)博士后

专业:概率论与数理统计、统计学、数据科学

招聘条件:

  1. 在相关专业已毕业或者即将毕业的博士; 985或境外名校相关专业博士毕业者优先;
  2. 具有较强的科研能力,能独立完成统计学或计量经济学研究等任务;
  3. 有数据分析的经验,精通Matlab, Python/R数据分析语言;
  4. 对变量选择、高维统计推断(含假设检验)、分位数回归,贝叶斯分析等有兴趣者优先。

 

岗位职责

  1. 从事与统计学相关的研究工作
  2. 发表具有国际竞争力的高水平学术论文;
  3. 协助课题组申报各类科研课题及承担相应的科学研究任务;

 

薪酬待遇及聘期:

  1. 博士后聘期两年。
  2. 博士后年薪5万元左右,含广东省补助15万元(税前)及深圳市生活补助6万元(税后),并按深圳市有关规定参加社会保险及住房公积金。博士后福利费参照学校员额内教职工标准发放。

 

其他待遇政策:

  1. 特别优秀者可以申请校长卓越博士后,年薪可达5万元。(含广东省及深圳市补助)
  2. 课题组提供优良的工作环境和境内外合作交流机会,博士后在站期间享受两年共计5万学术交流经费资助。
  3. 根据博士后具体科研工作业绩情况,可享受院系、课题组相应的科研绩效奖励。
  4. 课题组提供充足的科研支持,并协助博士后本人作为负责人申请中国博士后科学基金、国家自然科学基金及广东省、深圳市各级科研项目。

 

联系方式

有意向者请将以下信息整合为一个PDF文件:详细简历、成绩单、personal statement,research statement,最早可到岗时间。邮件发送至滕老师:tengyr@mail.sustech.edu.cn。

邮件标题请注明:蒋学军课题组-应聘岗位-本人姓名-所学专业。

 

 

统计与数据科学系成立于 2019年4月,目前共有科研教学系列教师 8人,其中有讲席教授1人,教授2人,副教授2人,Tenure-track助理教授2人,访问助理教授1人。本系有统计学和数据科学(筹)2个学科方向,包含生物统计、金融统计、实验设计、高维数据、随机矩阵、时间序列、概率论、数据科学等主要研究领域。本系的教师100%有境外学习或工作经历,包括1名国际数学家大会邀请报告人,1位国家自然科学奖二等奖获得者,1名国际数理统计学会会士,理事会常务理事,Medallion讲座演讲者。

本系志在为国家培养出思想活跃,创新意识和能力强,科研品味高,脚踏实地,有朝气,有理想的拔尖人才。系里已有统计学本科专业和统计学硕、博学位授予权,并在积极筹建数据科学与大数据本科专业。2019年南科大成功培养出了第一届38名统计学本科毕业生。系里的教师们在多种联培和南科大数学学科硕博点框架下已培养统计学硕士毕业生5名,现有在读统计学硕士生17名、博士生9名、博士后1名。随着本系的发展和师资力量的增强,研究生招生数目将逐年上升,招生方向也将包括数据科学与大数据技术。

本系目前正处于一个高速发展时期,师资力量在未来的几年内将大幅度增长。大数据时代的到来为统计和数据科学的发展带来了良好的机会。我们诚请国内外优秀的统计和数据科学学者加入我系的教师行列,为把我系建设成为一流的统计与数据科学系而共同奋斗。同时,我们热诚欢迎优秀的本科生、研究生、博士后到我系学习、研究。

 

统计与数据科学系:https://stat-ds.sustech.edu.cn/

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联系地址

慧园3栋522

办公电话

0755-88018687

电子邮箱

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