Mimi Zhang joined TCD as an assistant professor in 2017. She holds a B.Sc. in statistics from University of Science and Technology of China (2007 - 2011), and a Ph.D. in industrial engineering from City University of Hong Kong (2011 - 2014). Before joining TCD, she was a research associate at University of Strathclyde and Imperial College London. Her main research areas are machine learning and operations research, including cluster analysis, Bayesian optimization, functional data analysis, reliability & maintenance (engineering), etc. Visit Mimi’s profile page on the School of Computer Science and Statistics.
Mimi Zhang’s research is built on math, probability & statistics and algorithms, with applications in various fields (manufacturing, materials, health, etc.). A primary focus of her work lies in functional data analysis. A functional datum is not an individual value but rather a set of measurements/observations along a continuum that, taken together, are to be regarded as a single entity. In additive manufacturing, functional data analysis techniques can be used to analyze trends, patterns, and variability in printing parameters over time. Functional data analysis techniques can also be used for shape analysis of the geometric features of printed objects, understanding how geometric features vary along different sections of the printed object.
Expertise
Artificial Intelligence, Control Engineering, Data Analytics, Multi-variate Time Series Data Analysis, Process Monitoring and Control, Real-time Data Analytics, Reliability Analysis