Jizu Huang
News
[Aug. 4, 2024] Our paper ‘‘High order energy stable discrete variational derivative schemes for gradient flows,’’ has been accepted for publication in the IMA Journal of Numerical Analysis.
[Jul. 22, 2024] Our paper ‘‘A robust two-level overlapping preconditioner for Darcy flow in high-contrast media,’’ jointly with Doctor Changqing Ye et al., has been accepted for publication in the SIAM Journal on Scientific Computing.
[Jul. 20, 2024] Our paper ‘‘Phase Field Smoothing-PINN: a neural network solver for partial differential equations with discontinuous coefficients,’’ jointly with Doctor Rui He et al., has been accepted for publication in the Computers and Mathematics with Applications.
[Feb. 22, 2024] Our paper ‘‘Adaptive space-time domain decomposition for multiphase flow in porous media with bound constraints,’’ jointly with Doctor TianPei Cheng et al., has been accepted for publication in the SIAM Journal on Scientific Computing.
Research Interests
Numerical solvers for partial differential equations: in scientific and engineering computing, many problems can be modeled by partial differential equations. However, exact solutions to these equations are often unattainable, especially in complex geometries or with non-linearities. Numerical solvers provide a way to approximate these solutions with high accuracy, enabling us to simulate real-world systems, optimize designs, and predict outcomes in a variety of fields, from weather forecasting to aerospace engineering. My current interests are mathematics analysis and numerical solvers (including finite element, finite difference, and deep neural network method) for partial differential equations.
Parallel computing: parallel computing is a type of computation in which many calculations or the execution of processes are carried out simultaneously. Parallelism has long been employed in high-performance computing, but it's gaining broader interest due to the physical constraints preventing frequency scaling. As power consumption (and consequently heat generation) by computers has become a concern in recent years, parallel computing has become the dominant paradigm in computer architecture, mainly in the form of multi-core processors. My current interests are parallel algorithm for the large scale linear/nonlinear systems arising from solving partial differential equations.
Low-rank tensor decomposition: Low-rank tensor decomposition is a powerful technique that plays a critical role in various scientific and engineering disciplines. Tensors, which are multi-dimensional generalizations of matrices, often arise in applications like scientific computing and machine learning. However, the sheer size and complexity of tensor data make it challenging to store, process, and interpret. Low-rank tensor decomposition addresses this challenge by approximating tensors with simpler structures that capture the most important features while significantly reducing computational and storage requirements. This not only enables the efficient handling of large-scale data but also facilitates the extraction of meaningful patterns and dimensionality reduction. The importance of low-rank tensor decomposition lies in its ability to transform complex, high-dimensional problems into more tractable forms, thus making it indispensable in modern data-driven research and applications. My current interests are (quantum) tensor train low-rank decomposition and its applications in scientific computing.
Employment
Apr. 2019 – Present, Associate professor, Institute of Computational Mathematics and Scientific/Engineering Computing, Academy of Mathematics and Systems Sciences, Chinese Academy of Sciences, Beijing, China.
Jul. 2014 – Mar. 2019, Assistant professor, Institute of Computational Mathematics and Scientific/Engineering Computing, Academy of Mathematics and Systems Sciences, Chinese Academy of Sciences, Beijing, China.
Jul. 2012 – Jun. 2014, Postdoc research fellow, Institute of Software, Chinese Academy of Sciences, Beijing, China.
Education
Ph.D in Computational Mathematics, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Aug. 2007 – Jul. 2012
Dissertation: Multiscale Modeling and Algorithms for Heat Transfer Problems in Composite Materials (复合材料与结构综合热传输问题的多尺度模型与算法)
Advisor: Professor Li-Qun CAO (曹礼群)
Visiting Ph.D student: Commonwealth Scientific and Industrial Research Organisation (CSIRO), Mar. 2011 – Jun. 2011
Advisor: Sam Yang
B.Sc in Enviromental Engineering, College fo Enviromental Science and Engineering, Hunan University, Sep. 2000 – Jul. 2004
Awards
Member of Youth Innovation Promotion Association by CAS, 2018. (中科院青年创新促进会会员)
Students
Graduated Students
Dr. ZiBo Lu, from HeFei Univ. Tech., 2018-2023, First job after Ph.D.: Baidu(百度)
Current Students
Chi Zhang, from BeiJing Inst. Tech., Ph.D. Cand., 2021-
ZhongHao Sun, from Harbin Inst. Tech., Ph.D. Cand., 2022-
Junyuan He, from Nanjing Univ., Ph.D. Cand., 2023-
Yong Ma, from China Agricultural Univ., Ph.D. Cand., 2024-
Visiting Students
Jiali Zhang, from ChongQing Univ., 2018-2019
Jiehong Zhao, from Hunan Univ., 2018-2019
Yujia Luo, from ChongQing Univ., 2021-2022
Yanfu Chen, from Northwestern Polytechnical Univ., 2023-2023
Xixin Wu, from Northwestern Polytechnical Univ., 2023-2023
Tianpei Chen, from Hunan Univ., 2023-2023
Jiale Wu, from Northwestern Polytechnical Univ., 2023-2024
I am looking for students with mathematical background who are interested in pursuing Master's or Ph.D. degrees. Please send me an email (with a copy of your resume) for details.
Grants
Jan. 2024 – Dec. 2027, 镍基高温合金多物理场耦合建模与并行算法, (RMB 435,000, 国家自然科学基金委面上项目).
Jan. 2022 – Dec. 2026, 面向E级计算的数千万核可扩展非线性偏微分方程求解算法及其应用, (RMB 2,520,000, 国家自然科学基金委重点项目).
Jan. 2020 – Dec. 2024, 纤维增强仿生橡胶多尺度分析与优化设计, (PI, RMB 2,800,000, 中国科学院战略性先导科技专项C).
Jan. 2019 – Dec. 2022, The study of lattice Boltzmann models and parallel algorithms for multiphase flows problem, NSFC, No.11871069 (PI, RMB 570,000, 面上基金).
Jan. 2015 – Dec. 2018, Multiscale modeling and parallel algorithm for lattice Boltzmann equations, NSFC, No.11501554 (PI, RMB 190,000, 青年基金).
Jul. 2018 – Dec. 2021, 高通量并发式材料计算算法和软件 (RMB 450,000, 国家重点研发计划)
Jan. 2017 – Dec. 2021, 大规模结构有限元高效计算方法研究 (RMB 2,000,000, 中国科学院战略性先导科技专项B)
Academic Visits
Professor Xiao-Ping Wang, Hong Kong University of Science and Technology, HK, Jan. 2019 – Feb. 2019
Professor Yau-Shu Wong, University of Alberta, CAD, Jul. 2018 – Aug. 2018
Professor Xiao-Ping Wang, Hong Kong University of Science and Technology, HK, Feb. 2017 – May. 2017
Professor Xiao-Ping Wang, Hong Kong University of Science and Technology, HK, Jul. 2015 – Aug. 2015
Professor Xiao-Ping Wang, Hong Kong University of Science and Technology, HK, Feb. 2015 – Mar. 2015
Professor Xiao-Chuan CAI, University of Colorado Boulder, USA, Sep. 2012 – Feb. 2013
Teaching Experience
Sep. 2014 – Jun. 2015, Linear algebra, University of Chinese Academy of Sciences
Sep. 2015 – Jun. 2016, Linear algebra, University of Chinese Academy of Sciences
Sep. 2016 – Feb. 2017, Linear algebra, University of Chinese Academy of Sciences
Seb. 2017 – Jun. 2018, Linear algebra, University of Chinese Academy of Sciences
Seb. 2018 – Dec. 2018, Numerical Linear algebra, University of Chinese Academy of Sciences
Feb. 2019 – Jun. 2019, Linear algebra, University of Chinese Academy of Sciences
Seb. 2019 – Dec. 2019, Numerical Linear algebra, University of Chinese Academy of Sciences
Seb. 2020 – Dec. 2020, Numerical Linear algebra, University of Chinese Academy of Sciences
Seb. 2021 – Dec. 2021, Numerical Linear algebra, University of Chinese Academy of Sciences
Seb. 2022 – Dec. 2022, Numerical Linear algebra, University of Chinese Academy of Sciences
Seb. 2023 – Dec. 2023, Numerical Linear algebra, University of Chinese Academy of Sciences
Contact
P.O. Box 2719, No. 55, ZhongGuanCun East Road
HaiDian District, Beijing 100190, China
Tel: (86) 8254-1018
Fax: (86) 8254-1016
Office: Room 410, LanBai Building
Email: huangjz @ lsec.cc.ac.cn