Yingrui (Rae) Chen
Title
Matrix Real-Coded Genetic Algorithm and It’s Application on Synthetic Data Generation
PhD summary
My research is about designing a new synthesis method to generating synthetic data through genetic algorithms and testing the effectiveness and utility of this method. Genetic Algorithms (GA) are learning method that simulates evolutionary processes in biological systems. It has been successfully used in solving high-dimensional and dynamic problems. Data synthesis a mechanism in data privacy protection. It controls disclosure risk of datasets of personal or confidential data and provides simulated data files derived from the original data with near zero risk re-linkage or re-identification.
Biography
Previously studied MSc Operational Research and Risk Analysis in Manchester Business School. Completed BSc Mathematics in Loughborough University with First Class Honor.
Dates
January 2016-December 2018
Funding
Self-funded
Publications
- Y. Chen, M. Elliot and J. Sakshaug, 2016. A Genetic Algorithm Approach to Synthetic Data Production, in Proceedings of the 1st International Workshop on AI for Privacy and Security. Article No. 13.
- Y. Chen, M. Elliot and J. Sakshaug, 2017. Genetic Algorithms in Matrix Representation and Its Application in Synthetic Data, UNECE Work Session on Statistical Data Confidentiality 2017.
Supervisors
- Prof Mark Elliot
- Dr Duncan Smith (previous supervisor: Dr Joseph Sakshaug)