领域:新一代信息技术产业 学校:东南大学职称:副教授
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1. 国家自然科学基金青年项目,11501102,基于紧支径向基函数的支持向量机多尺度算法及其应用,2016/01-2019/01,18万元,主持。
2. 江苏省科技厅基础研究计划(自然科学基金)青年基金项目,BK20150594,球面上的多尺度正则化拟合算法及其数值实现 ,2015/07-2018/06,20万元,主持。
3. 国家自然科学基金面上项目,11871149,Banach空间基于光滑惩罚项的正则化算法及其应用,2019/01-2022/12,52万元,主持。
3. 国家自然科学基金面上项目,带斜导数边界条件的偏微分方程定解问题的边界反演,2017/01-2020/12,48万元,参与。
4. 国家自然科学基金面上项目,带有随机输入的偏微分方程反问题不确定性量化方法,2018/01-2021/12,48万元,参与。
2019 东南大学至善青年学者
2018 东南大学第25届授课竞赛二等奖,江苏省青蓝工程青年骨干教师
2017 东南大学微课竞赛二等奖
2016 上海市优秀博士学位论文
2014 上海市优秀毕业生,第六届反问题理论与计算分析研讨会浪潮青年学术奖
2012 中国计算数学协会优秀青年论文竞赛二等奖
1. 陈南,钟敏,许伯熹,带正则化项的时间序列聚类算法及其应用,复旦学报(自然科学版),51(2012),56-63.
2. Zhong M.,Lu S., Cheng J., Multiscale analysis for ill-posed problems with semi-discrete Tikhonov regularization, Inverse Problems, 28(6),2012,19-37.
3. ZhongM., Loy R. J., Anderssen R. S., Approximating the Kohlrausch function by sums ofexponentials, ANZIAM J, 54(04), 2013, 19-37.
4.Jin Q.,Zhong M.,On the iteratively regularized Gauss-Newton method in Banach spaces withapplications to parameter identification problems, Numer. Math., 124(4), 2013, 647-683.
5.Xu B., Lu S.,Zhong M., Multiscale support vector regression method in Sobolev spaces onbounded domains, Applicable Analysis, 94(3), 2014, 1-22.
6. Jin Q.,Zhong M., Nonstationary iterated Tikhonov regularization in Banach spaces with general convex penalty term, Numer. Math., 127(3), 2014, 485-513.
7.Hon Y.C., Schaback R.,Zhong M., The meshless kernel-based method of lines for parabolicequations, Comput. Math. Appl. 68(12), 2014, 2057-2067.
8.Zhong M.,Hon Y. C., Lu S., Multiscale support vector approach for solving ill-posed problems, J. Sci. Comput.64, 2015, 317-340.
9.Zhong M., Wang W., A global minimization algorithm for Tikhonov functionals with p- convex(p>=2)penalty terms in Banach spaces, Inverse Problems, 32, 2016, 104008 (30pp).
10.Zhong M., Liu J.J., On the reconstruction of media inhomogeneity by inverse wavescattering model, Sci. China. Math., 60(10), 2017, 1825-1836.
11.Zhong M., Le Gia Q.T., Wang W., A multiscale support vector regression method on sphereswith data compression, Applicable Analysis,98(8),2019, 1496-1519.
12.Zhong M., Wang W., A regularizing multilevel approach for nonlinear inverse problems, Appl. Numer. Math.,135, 2019, 297-315.
13.Zhong M., Jin Q., Wang W., Regularization of inverse problems by two-point-gradient methods with convex constraints.,Numer.Math, 143(3), 2019, 713-747.