Hot Topic Speakers

Prof. Sungrim Seirin-Lee (Kyoto University)

Prof. Seirin-Lee obtained her PhD from Okayama University, Japan in 2010. During the doctoral course, she studied abroad at the Center for Mathematical Biology, Mathematical Institute, Oxford University. Afterward, she undertook postdoctoral training as a JSPS PD fellow at the University of Tokyo and RIKEN. She was appointed as an Assistant Professor in 2014, promoted to Associate Professor in 2017, and became a Full Professor in 2020 at Department of Mathematics, Hiroshima University. In 2021, she was appointed as a Full Professor at the Kyoto University Institute for Advanced Study (KUIAS), and in 2023, she concurrently joined the Graduate School of Medicine, Kyoto University, as a Full Professor. Her main research is in mathematical medicine, focusing on dermatology, immunological diseases, and spatial immunology, as well as on applied mathematics in the field of pattern formation.

Website: https://ashbi.kyoto-u.ac.jp/bimed-math/

Dr. Tomoki Uda (The University of Toyama)

Dr. Tomoki Uda is a Lecturer in the Department of Mathematics at the University of Toyama and a member of the Japan Society for Industrial and Applied Mathematics (JSIAM). Within JSIAM, he serves as a Committee Member of the Activity Group on Topological Data Analysis and is on the Editorial Board of the JSIAM Bulletin. His research is in numerical analysis and topological data analysis (TDA), with a focus on the mathematical foundations and computational aspects of persistent homology. He has contributed to stability theory and algorithmic developments that support the reliable use of TDA in scientific applications. One of his primary research directions is Topological Flow Data Analysis (TFDA), a framework that applies topological methods to investigate dynamical systems and flow data. Applications include meteorology and oceanography, where topological techniques have been used to describe and compare complex spatio-temporal patterns. He is currently working on the development of anisotropic persistent homology methods through ellipse cloud filtrations. Recently, his interests have further extended to optimal transport and magnitude homology. His work highlights both theoretical soundness and computational feasibility, aiming to broaden the scope of TDA as a robust methodology for data analysis.