Research Seeds Collection
Discover mathematical models from data.
Research
We use mathematical models to understand the mechanisms by which complex patterns and structures appear in nature are formed. In particular, we are interested in soft materials, such as polymers, liquid crystals, and colloids, that form structures through self-assembly. These structures can be found in a wide range of fields, from materials science that supports our lives to biology, such as the patterns created by cells and cell populations. We are conducting research to understand the mechanisms of structure formation by constructing mathematical models from data using machine learning techniques and by integrating mathematical models with machine learning.
Research achievements related to the aforementioned seed
i) Uyen Tu Lieu and Natsuhiko Yoshinaga, “Dynamic control of self-assembly of quasicrystalline structures through reinforcement learning” Soft Matter, 21, 514-525 (2025)
ii) Natsuhiko Yoshinaga and Satoru Tokuda, “Bayesian Modeling of Pattern Formation from One Snapshot of Pattern” Physical Review E, 106, 065301 (2022)
Faculty members involved in this research project
Natsuhiko Yoshinaga
Natsuhiko YoshinagaDepartment of Complex and Intelligent Systems; Complex Systems Information Science Professor