报告题目：How to make computations faster? 如何使计算更快？

演讲摘要：待发布

讲者简介：Eugene Tyrtyshnikov，俄罗斯科学院院士，俄罗斯数学家，教授，物理与数学科学博士，俄罗斯科学院马尔丘克数值数学研究所所长，罗蒙诺索夫莫斯科国立大学计算数学和计算机科学计算技术和建模系主任。主要研究成果包括图普利茨及相关矩阵谱分布分析的矩阵框架、低秩近似的最大体积概念、跨行列近似和多维问题的张量训练算法。 莫斯科罗蒙诺索夫国立大学年度最佳教师（2014年），索博列夫数学研究所“数学伟大贡献”金奖（2019年），Sber“数字宇宙” 科学奖（2023年）。2014-2015年国际会计准则理事会会士，《计算数学与数学物理杂志》主编，线性代数及其应用副主编（2000-2023）。 Calcolo，Sbornik Mathematics，Russian Journal Of Numerical Analysis And Mathematical Modeling，Syberian Journal Of Numerical Mathematics编辑委员会成员。 Prof. EugeneTyrtyshnikov, Academician of Russian Academy of Sciences (since 2016). Director of Marchuk Institute of Numerical Mathematics of Russian Academy of Sciences, Professor and Chairman at the Lomonosov Moscow State University. Best teacher of the year at the Lomonosov Moscow State University (2014). Gold Medal "For Great Contributions in Mathematics" by Sobolev Institute of Mathematics (2019). Sber Scientific Prize in the nomination “Digital Universe” (2023). Member of ILAS Board in 2014-2015. Editor-in-chief of Journal of Computational Mathematics and Mathematical Physics. Associate editor of Linear Algebra and Its Applications (2000-2023). Member of editorial boards of Calcolo, Sbornik Mathematics, Russian Journal of Numerical Analysis and Mathematical Modelling, Syberian Journal of Numerical Mathematics. Main results include the matrix framework for the analysis of spectra distribution of Toeplitz and related matrices, maximal volume concept for low-rank approximation, cross row-column approximations and tensor-train algorithms for multidimensional problems.