Institute of Statistical Mathematics, Japan
Advances in Polymer Informatics: Challenges and Potentials
Abstract: Machine learning technologies in materials informatics on polymeric materials are described based on the study of thermophysical properties of polymers. One of the highest barriers to the implementation of materials informatics in polymer research is the lack of a digital database that can be used for data-driven research. We are building a fully automated computational pipeline for molecular dynamics simulations and developing the world's largest and most comprehensive database of polymer properties.
Ryo Yoshida, a Professor at the Institute of Statistical Mathematics (ISM), has served as the director of Data Science Center for Creative Design and Manufacturing in ISM since the center’s opening in July 2017. After receiving his Ph.D. degree in statistical science from the Graduate University for Advanced Studies in 2004, he worked as a Project Assistant Professor for the Human Genome Center at Institute of Medical Science, the University of Tokyo – a position he has maintained before joining the ISM in 2007. In addition, he serves as an invited researcher for National Institute for Materials Science (NIMS). He is trying to discover new materials with innovative properties, using advanced machine learning techniques.