Research Director

Ichigaku Takigawa

Graduate School of Information and Technology, Hokkaido University
Associate Professor

Outline

The goal of this proposal is to establish fast and accurate data-driven prediction of electronic properties of substances and materials. Given the digital exhaust of observed and computer-simulated data, advances in material sciences can be accelerated by making sense and making full use of these rich data. By leveraging the latest advances in deep learning technologies, this project aims to computationally enable comprehensive screening of a wide variety of substances and materials, and also provide evidence-based insights on factors defining desirable properties toward inverse design.