Data Science Seminar Series – TRU Newsroom
Modelling change over time
Dr. Xiaoping Shi, Dept of Mathematics & Statistics, TRU
Change happens according to its own pattern of operation, whether you accept the change or not. A response to such changes, especially bad ones, is to understand the pattern of such changes. Some studies have shown that: 1) The S wave always arrives after the P wave inside the earth; 2) DNA copy number is constantly changing through the process of mutation; 3) Human plasma proteome changes with age; 4) Our lungs change colour as we age; 5) The brain’s structure changes as new memories have been gained; 6) The spread of covid-19 possesses a sort of circular memory characteristic, a circumference from short-term memory to long-term memory and then to a new memory (see graph-clustering-system.com). This talk presents the statistical inference in five models to answer whether and when the models change.
Dr. Xiaoping Shi received his PhD in Statistics from York University. He then did a postdoctoral fellowship at the University of Toronto, where he was awarded a teaching position, and later at York University and St. Francis Xavier University. Since 2015, he has been an Assistant Professor in the Department of Mathematics and Statistics at TRU.
His current areas of expertise include change point analysis, saddle point approximation, inverse moment approximation, two-sample inference, and cluster analysis. He makes contributions that make sense and enjoys working with statisticians, data scientists, and computer scientists who share common interests. His philosophy is to stimulate students’ curiosity by presenting them with important questions and interesting data. Since starting at TRU, he has supervised/co-supervised 9 students in 11 research projects with funding from NSERC and internal TRU grants. He continues to seek grants to support research projects and to improve the quality of research outputs.
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