Synthetic Population As Digital Twin Technology for Real Scale Social Simulations

Synthetic Population as Digital Twin Technology for Real-Scale Social Simulations Professor Tadahiko Murata, Cybermedia Center of Osaka University, Japan - IEEE Fellow A person smiling at the camera Description automatically generatedDr. Tadahiko Murata is a Professor at Cybermedia Center of Osaka University, Japan. In Osaka University, he has classes in Division of Electronic and Information Engineering for undergraduate students and Graduate School of Information Science and Technology for graduate students. He was President of Japanese Society for Evolutionary Computation from 2020 to 2022. He is currently Vice President of Organization and Planning in IEEE SMC Society and Vice President in Japan Society for Fuzzy Theory and Intelligent Informatics. He is IEEE Fellow. Abstract: In order to realize the digital twin for communities or regions in the cyber space, we need to obtain information on household members in the target area. However, attributes such as age, school, workplace, and income of household members are their privacy, it is difficult to utilize them in a digital twin. Synthetic population method synthesize or generates those personal data only from publicly released statistics. In the pandemic of Covid-19, a lot of researcher synthesize those household information from the statistics and simulate Covid-19 spreading in the target region. In this talk, I show several application examples of synthetic population in Japan.