明炬 - 华中科技大学 - 数学与统计学院

个人简介

I am a professor at the School of Mathematics & Statistics, Huazhong University of Science and Technology(HUST). I obtained my BS degree at the Department of Mathematics, Wuhan University. I earned my Ph.D at Iowa State University in computational mathematics in 2009, superwised by Lisheng Hou. My thesis is about optimal control of stochastic Navier-Stokes flow. I then worked with Max Gunzburger in Florida State University at the Department of Scientific Computing as a post-doctoral research associate from 2009 to 2012. My primary research interests there centered around uncertainty quantification, CFD, and stochastic control. Supported by Prestigious Outstanding Young Fellow Award， I worked as an assistant professor at Beijing Computational Science Research Center (CSRC) from 2013 to 2017. Then from 2017, I transferred to HUST as a professor. Recent Activities: FIU Conference on Applied Mathematics, Florida international university, Miami, USA, Jan 03-06, 2018 The SIAM Conference on Applied Linear Algebra, Hong Kong Baptist University, Hong Kong, May 4-8, 2018 2018 最优控制与反问题研讨会，Wuhan University, Wuhan, March 2018 不确定性量化和高性能计算研讨会，同济大学，上海，2018,06,16-17 Workshop in Hornor of Prof.Vincent J. Ervin’s 60th Birthday, Center for Mathematical Science, HUST, Wuhan, 07/03/2018 随机计算热点问题研讨会，吉林大学，长春，2018,06,22-24 Workshop on Differential Equations on Networks and Related Problems, Zhejiang University, Hang Zhou, China July 13-14, 2018. 中国计算数学年会，哈尔滨工业大学，哈尔滨，Aug.,2019 随机偏微分数值计算研讨会，吉林大学天元中心，长春，Sep.14-15, 2019

研究领域

s include uncertainty quantification, optimal control, finite element methods, numerical analysis, stochastic partial differential equations

近期论文

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A discontinuous Galerkin method for stochastic Cahn–Hilliard equations, Computers & Mathematics with Applications, 75(6), 2018, pp 2100-2114 The multi-level Monte Carlo method for simulations of turbulent flows, Monthly Weather Review, DOI:10.1175 Asymptotically Compatible Schemes for Stochastic Homogenization, SIAM Journal on Numerical Analysis, 56(3), 2018, pp1942–1960. Bayesian approach to inverse time-harmonic acoustic scattering with phaseless far-field data, Inverse Problems 36 (2020) 065012 (30pp). Accelerating the Bayesian inference of inverse problems by using data-driven compressive sensing method based on proper orthogonal decomposition,Electronic Research Archive, 2021-6, Bayesian approach to inverse time-harmonic acoustic obstacle scattering with phaseless data generated by Point Source Waves, accepted by Computer Methods in Applied Mechanics and Engineering Cluster-based gradient method for stochastic optimal control problems with elliptic PDE constraint , accepted by Numerical Method for Partial Differential Equations