SciPy Japan's Schedule will be available August 11!
Professor, The Institute of Statistical Mathematics, Research Organization of Information and Systems
Machine Learning Technologies for Accelerating Discovery of Innovative Materials
The open source software XenonPy provides machine learning modules for various tasks in materials informatics. In this talk, I introduce some important technologies of machine learning, which would be key drivers to the next frontier of creative design and manufacturing in materials science. In addition, the potential applicability of XenonPy is illustrated on the discovery of new polymers exhibiting novel thermophysical properties and application to process control of the microstructure of composite materials, and so on.
Ryo Yoshida, a Professor for Department of Data Science 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. 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 after joining the ISM in 2007. In addition, he serves as an invited researcher for National Institute for Materials Science (NIMS). He received the IIBMP Research Encouragement Prize (2016 and 2017). He has the experience of using his expertise in data science for research work in both biology and materials science. He is leading the development of XenonPy–a machine learning platform for materials science. He is devoted to foster and practice machine learning technologies for creative design and manufacturing through industry-academia collaboration. In addition, he is devoted to creating the scientific foundation of materials informatics for polymeric materials and quasicrystals through some research projects founded by the JST-CREST program and the Japan Society for the Promotion of Science (JSPS).
10/31 13:30 - 14:30
Professor, Faculty of Data Science, Shiga University
Deputy Director of the Center for Data Science Education and ResearchFormer head of the Business Analysis Center, Osaka Gas Co.
The Business Supportive Data Scientist Work Approach
How can you make data analysis more than just an analysis, but an analysis leading to business outcomes? Based on my experience of repeated failures in my previous jobs, I’ve learned the causes of what goes wrong and the types of work that can be done to overcome them. The key point is to turn tacit knowledge into formal knowledge before embarking on data analysis. In this talk I would like to systematize this method.
Graduated from Kyoto University in 1991 with a degree in Applied Systems Science and joined Osaka Gas. In 1998 started research at the Lawrence Berkeley National Laboratory in the U.S working on energy consumption data analysis. After returning to the company, he worked on promoting business reform through data analysis. In 2011, he served as director of the Business Analysis Center and established the data analysis organization. He was awarded the first Data Science of the Year by Nikkei Information Strategy, April 2018. He has been in his present position. Doctor of Engineering and Economics. He is the author of multiple books related to the power of analysis for changing company. He has also appeared on NHK professional documentary show.