邓明宇讲师

发布者:华原原发布时间:2025-09-26浏览次数:14


姓名

邓明宇

职称、学位

讲师、博士

邮箱

my_deng@stu.ecnu.edu.cn

专业

数量经济学

研究方向


空间计量理论

Kaczmarz算法

邓明宇,男,中共党员,199411月生,安徽合肥人,应用经济学博士。现为安徽财经大学讲师,研究领域与方向为空间计量理论,随机前沿分析,Kaczmarz 随机算法。


教育背景:

2020.09--2024.06(博士):对外经济贸易大学,数量经济学,应用经济学博士

2017.09--2020.06(硕士):华东师范大学,计算数学,理学硕士

2013.09--2017.06(本科):安徽师范大学,数学与应用数学,理学学士


工作经历:

2024.07 至今:安徽财经大学,统计与应用数学学院,合肥高等研究院,讲师


一、主讲课程

为本科生开设《统计学》《概率论》等课程;为研究生开设《中级计量经济学》等课程。


二、科研项目(所有或者近三年)

1.主持安徽省哲学社会科学青年项目“虚拟集聚视角下安徽省创新要素空间配置效率与长三角协同效应研究”(AHSKYQ2024D077),2025.3,在研。


三、论文(所有或者近三年)

[1]Deng, M. Y., Kutlu, L. Spatial stochastic frontier model with stochastic weighting matrix. Online in Empirical Economics, 2025, DOI: https://doi.org/10.1007/s00181-025-02815-z.

[2]Tan, L. Z., Deng, M. Y., Qiu J. L., & Guo, X. P., On the adaptive deterministic block coordinate descent method with momentum for solving large linear least-squares problems. Accepted by Journal of Computational Mathematics.

[3]Deng, M. Y., Fu, Y., Kutlu, L., & Wang, M. Goodness of fit tests in spatial autoregressive stochastic frontier models. Econometric Reviews, 2025, 44(8): 1234–1256.

[4]Deng, M. Y., Kutlu, L., Wang, M. Skewness-based test diagnosis of technical inefficiency in spatial autoregressive stochastic frontier models. Journal of Productivity Analysis, 2024, 62(1): 53–70.

[5]Deng, M. Y., Wang, M. X., Artificial regression test diagnostics for impact measures in spatial models. Economics Letters, 2022, 217.

[6]Tan, L. Z., Deng, M. Y., Guo, X. P., On multi-step greedy randomized Kaczmarz method for solving large sparse linear system, Communications on Applied Mathematics and Computation, 2025, 7: 1580–1597.

[7]Tan, L. Z., Guo, X. P., Deng, M. Y. & Chen, J. R., On the adaptive deterministic block Kaczmarz method with momentum for solving large-scale consistent linear systems, Journal of Computational and Applied Mathematics, 2025, 457: 116328.

[8]Deng, M. Y., Ding, W. Y., Guo X. P., Modified splitting methods for solving non-homogenous multi-linear equations with M-tensors. Pacific Journal of Optimization, 2022, 18(1): 91–117.

[9]Deng, M. Y., Guo, X. P., On HSS-Based Iteration Methods for Two Classes of Tensor Equations. East Asian Journal on Applied Mathematics, 2020, 10(2): 381–398.