Real-Scale Social Simulations Using Societal Synthetic Populations in Digital Twin
It is essential for researchers to consider human factors in real-scale social simulations that take into account people living and working in target communities. In order to do so, researchers need to know attributes of living and working people such as age, sex, race, living place, occupation, income and workplace. However those attributes are a kind of privacy data that are not available to researchers. To tackle with such difficulty in accessibility, data synthesis is getting attentions recently. Data synthesis is a method to synthesize data based on the statistical characteristics of collected data. The lecturer gives a talk how to synthesize the population data using statistics, and several applications of synthesized population data in real-scale social simulations including COVID-19 counter-measures.
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- Ulster University Belfast Campus
- Belfast, Northern Ireland
- United Kingdom
- Building: BC
- Room Number: BC-03-206
- Contact Event Host
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m.garcia-constantino@ulster.ac.uk
- Co-sponsored by Ulster University
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Tadahiko of University of Osaka, Japan
Real-Scale Social Simulations Using Societal Synthetic Populations in Digital Twin
Real-Scale Social Simulations Using Societal Synthetic Populations in Digital Twin
This lecturer shows how to synthesize the population data using statistics, and several applications of synthesized population data in real-scale social simulations including COVID-19 counter-measures. Latest research work in synthetic population and its applications are shown in this talk.
It is essential for researchers to consider human factors in real-scale social simulations that take into account people living and working in target communities. In order to do so, researchers need to know attributes of living and working people such as age, sex, race, living place, occupation, income and workplace. However those attributes are a kind of privacy data that are not available to researchers. To tackle with such difficulty in accessibility, data synthesis is getting attentions recently. Data synthesis is a method to synthesize data based on the statistical characteristics of collected data. The lecturer gives a talk how to synthesize the population data using statistics, and several applications of synthesized population data in real-scale social simulations including COVID-19 counter-measures.
Biography:
Tadahiko Murata (IEEE Fellow) is a full professor at the University of Osaka (UOsaka). In UOsaka, he is working for D3 Center that is a supercomputing, Graduate School of Information Science and Technology, and Undergraduate School of Engineering. His interests include multi-objective optimization, social simulations, digital twin, and high-performance computing. He was President of Japanese Society for Evolutionary Computation from 2020 to 2022, and Vice President for Organization and Planning, IEEE SMCS from 2022 to 2025, and Vice President of Japan Society for Fuzzy Theory and Intelligent Informatics from 2023 to 2025.
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