Regular biography
Yoshihito Kazashi is a Lecturer in Numerical Analysis and Data Science in the Department of Mathematics at The University of Manchester. Prior to joining the university in July 2025, he was a Strathclyde Chancellor's Fellow at the University of Strathclyde, where he was a member of the Numerical Analysis group. He also held postdoctoral positions at Universität Heidelberg and EPF Lausanne. Kazashi obtained his PhD at UNSW Sydney and completed his undergraduate degree at the University of Tokyo. His research focuses on numerical analysis and data science, with contributions to areas such as error bounds, quadrature methods, and density estimation in high-dimensional spaces.
Scholar-generated biography
Yoshihito Kazashi is a researcher at the University of Manchester with expertise in high-dimensional problems, numerical analysis, and uncertainty quantification. His work focuses on developing efficient numerical methods for solving complex mathematical problems, particularly in the context of stochastic partial differential equations and uncertainty quantification. Kazashi's research includes the application of quasi-Monte Carlo methods, lattice-point interpolation, and dynamical low-rank approximations to improve the accuracy and efficiency of numerical solutions. His publications explore the theoretical foundations and practical implementations of these methods, contributing to the advancement of computational mathematics and its applications in scientific computing.