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Probability Theory and Mathematical Statistics

Time:Oct 12, 2023 Author: Clicks:

Nengxiang Ling

Nengxiang Ling is a professor and doctoral supervisor in the School of Mathematics at Hefei University of Technology. He received the B.S degree in mathematics from Anhui Normal University in 1986, and studied the postgraduate courses of probability and statistics at Anhui University from 1991 to 1992. In 2004, he received the M.S degree in applied mathematics from Hefei University of Technology. In addition, from July 2013 to August 2013, he visited the School of Mathematics, University of Adelaide in Australia and worked with Prof. of Statistics, Zudi Lu. Nengxiang Ling's major research interests include functional data analysis (FDA), statistical inference for non/semi parametric regression model, high dimensional factor modeling, Bayesian statistics, probability limit theory. He also presided over the key project funded by the Social Science Foundation of China, as well as the project funded by the Natural Science Foundation of China respectively, etc.

Email: hfut.lnx@163.com

Selected publications:

[1] Jiang Z,Y., Ling N.X., Lu Z.D., Tjøstheim D., Zhang Q., (2020), On bandwidth choice for spatial data density estimation, Journal of the Royal Statistical Society: Series B (Statistical Methodology), 82 (3), 817-840.

[2] Ling N. X., Aneiros G., Vieu, P. (2020), kNN estimation in functional partial linear modeling, Statistical Papers, 61(1), 423–444.

[3] Ling N. X., Cheng, L.L., Vieu P., Ding H. (2022), Missing responses at random in functional single index model for time series data, Statistical Papers, 63(2), 665-692.

[4] Yang S. Q., Ling N.X. (2023), Robust projected principal component analysis for large-dimensional semiparametric factor modeling, Journal of Multivariate Analysis , 195: 105155.

[5] Wu C.Q., Ling N. X., Vieu P., Liang W. J. (2023),

Partially functional linear quantile regression model and variable selection with censoring indicators MAR, Journal of Multivariate Analysis, 197: 105189.

[6] Ling N. X. and Vieu P. (2018), Nonparametric modelling for functional data: selected survey and tracks for future, Statistics, 52 (4) , 934-949.


Zhaoli Jia

Zhaoli Jia was graduated from the Department of Finance and Statistics of University of Science and Technology of China with a PhD. She has presided over three provincial and ministerial projects, one provincial teaching reform project, and published more than 20 papers in the field of probability statistics, and her current research interests are in the neighborhood of financial stochastic analysis and other areas. Students who are interested in these topics can contact her via E-mail: jiazhaoli@hfut.edu.cn.

Selected publications:

[1] WuHuojun,Jia Zhaoli*,Yang Shuquan, PricingVariance Swaps under Double Heston Stochastic Volatility Model with StochasticInterest Rate,Probability in the Engineering and Informational Sciences, 2022, 36:564–580. (corresponding author)

[2] Luo Qiang,Jia Zhaoli*, Analysis of parametric and non-parametric option pricing models, Heliyon,2022, 8, e11388. (corresponding author)

[3] YangShuquan , Jia Zhaoli *, Wu Qianqian , Homotopy Analysis Method for PortfolioOptimization Problem Under the 3/2 Model, Journal of Systems Science and complexity,2021,34:1087-1101. (corresponding author)

[4] JiaZhaoli and Bi Xiuchun, Zhang Shuguang*, Pricing variance swaps under stochasticvolatility with an Ornstein-Uhlenbeck process, Journal of Systems Science andComplexity, 2015.,28(6): 1412-1425.

[5] Jia Zhaoli and Zhang Shuguang*, Pricing convertible bonds andchange of probability measure[J], Journal of Systems Science and Complexity, 2013,26(6):968-977.


Li Cao

Li Cao is an Associate Professor in the Department of Statistics at Hefei University of Technology. She graduated from Wuhan University in 2012 with a doctoral degree in Probability Theory and Mathematical Statistics. She was the principal investigator for two projects funded by the National Natural Science Foundation of China (No. 11326205 and No. 11401156). Her primary research areas include fractal geological statistics and spatiotemporal data statistical analysis. In addition to her research activities, she is actively engaged in teaching both undergraduate and graduate courses, which include Probability Theory, Econometrics, Mathematical Statistics, Probability Theory and Mathematical Statistics, and Advanced Mathematics.

Email: caoli1984@hfut.edu.cn

Selected publications:

[1] L. Cao, L. F. Xi*, Y. P. Zhang, estimate of convolution transform of singular measure by approximate identity, Nonlinear Analysis, 2014, 94:148-155.

[2] L. Cao, Some asymptotic properties of the convolution transforms of fractal measures, Acta Mathematica Scientia, 2012,32(6):2096-2104.

[3] L. Cao, X. G. He*, Dimensional results for the Moran-Sierpinski gasket, Wuhan University Journal of Natural Sciences, 2012,17(2): 93-96.

[4] L. Cao, X. G. He*, Some dimensional results for cartesian products of homogeneous Moran sets, Acta Mathematicae Applicatae Sinica, 2012, 28(4): 673-680.


Qianqian Wu

Qianqian Wu received her Bachelor degree of science advanced with honours and Ph.D. both from Monash University in Australia in 2011 and 2015. She was the principal investigator for two grants funded by national natural science foundation of China and Anhui provincial natural science foundation from 2017-2019. She has published more than 10 papers in the field of mathematical biology etc., and her current research interests are Bayesian statistical inference, time series forecasting, mathematical biology especially in the area related to gene regulatory networks. Anyone who is interested in such topics can contact her by email (qian-qian.wu@hfut.edu.cn).

Selected publications:

[1] Qianqian Wu, Kate Smith-Miles, Tianshou Zhou and Tianhai Tian, Stochastic modeling of biochemical systems of multi-step reactions using a simplified two-variable model. BMC Systems Biology, 7(4):s14, 2013.

[2] Qianqian Wu, Kate Smith-Miles and Tianhai Tian, Approximate Bayesian computation schemes for parameter inference of discrete stochastic models using simulated likelihood density. BMC Bioinformatics, 15(S12):s3, 2014.

[3] Qianqian Wu, Feng Jiang and Tianhai Tian, Sensitivity and robustness analysis for stochastic model of Nanog gene regulatory network. International Journal of Bifurcation and Chao, 25(07), 2015.

[4] Qianqian Wu and Tianhai Tian. Stochastic modeling of biochemical systems with multistep reactions using state-dependent time delay: [J]. Scientific Reports, 2016, 6.

[5] Wang J, Wu Q, Hu X T, et al. An integrated approach to infer dynamic protein-gene interactions - A case study of the human P53 protein. [J]. Methods, 2016, 110:3-13.

[6] Wu Q, Wang J. Thresholds and critical exponents of explosive bond percolation on the square lattice[J]. International Journal of Modern Physics C, 2022(07),33.



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