I am an MPhil student in Data Intensive Science at the University of Cambridge. Previously, I began my graduate studies at the University of Tokyo under the supervision of Yutaka Matsuo. I am currently on a one-year leave from UTokyo to pursue my MPhil at Cambridge. I obtained my bachelor's degree in Mathematical Sciences with a minor in Cognitive Science from UTokyo, graduating as the valedictorian of the department. I was fortunate to be advised by Masaaki Imaizumi and had the pleasure of collaborating with Shinji Ito.

Previously, I worked on deep learning theory, focusing on the topological and dynamical properties of machine learning models. I am currently exploring topics at the intersection of physics, cognitive science, and machine learning, with a particular interest in applying machine learning to algebraic geometry and building neural data processing (encoding/decoding) models with strong generalizability (e.g., robust to representation drift). My current research interests include:

Representation drift in chronic neural data

Cross-individual generalization in neural models

Bridging moduli spaces and metrics (as well as topological properties) on Calabi–Yau manifolds