Workshop for topological optimization and machine learning

整理番号	2025a006
種別	若手・学生研究-研究集会（Ⅰ）
研究計画題目	Workshop for topological optimization and machine learning
研究代表者	Keunsu Kim（Institute of Mathematics for Industry, Kyushu University.・Postdoctoral researcher）
研究分野のキーワード	Topological optimization, Constraint, (Non)-convex problem.
目的と期待される成果	Research in the 2010s focused on achieving an integration of TDA (Topological Data Analysis) and ML (Machine Learning). The typical approach involved applying TDA to extract topological and geometrical information from a given dataset and transforming it into a vector format suitable as input for ML models. In this setup, TDA served as a preprocessing step for ML, with no involvement of ML during the TDA process. Since the 2020s, there has been growing interest in what is known as topological optimization, where ML actively participates in the TDA process to better capture the characteristics of the data. The objective of this conference is to bring together researchers from different disciplines related to TDA and ML. To achieve this, we aim to invite experts in TDA and optimization, as well as industry professionals, to share insights on current research trends and foster interdisciplinary exchange. This conference will provide an opportunity to uncover key topological optimization challenges based on the ideas of experts and industry practitioners, thereby advancing the integration of TDA and ML research. Notably, as the organizer has academic roots in Korea, the conference will invite Korean mathematicians and industry professionals, potentially contributing to enhanced academic and industrial collaboration between Japan and Korea.
組織委員(研究集会) 参加者(短期共同利用)	Keunsu Kim（Institute of Mathematics for Industry, Kyushu University・Postdoctoral researcher） Jae-Hun Jung（Department of Mathematics, POSTECH・Professor）