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Jun Yu is a Full Professor in Mathematical Statistics with a focus on Statistical Learning and Inference related to Spatiotemporal Data. He leads a research group that addresses theoretical problems in data science through the development of statistical learning methods and their applications in various fields such as atmospheric icing, the automobile industry, biomedical engineering, climate research, epidemiology, forestry, geochemistry, hydrology, radiation oncology, spatial ecology, and sports science. His primary research interests include sparsity, compressive sensing, hierarchical spatiotemporal modeling, and statistical inference techniques. He has published extensively on wavelet theory and its applications in signal and image analysis. Additionally, Yu has been actively involved in several research projects, including AI-driven cell sorting, generative mixture linear models, and statistical learning in chronosilviculture. He has taught courses in Mathematical Statistics and Data Science at various education levels and has utilized multiple languages in his teaching, including English, Swedish, and Chinese.
Umeå University • Umeå, Sweden
Full Professor at the Department of Mathematical Statistics, focusing on statistical learning and inference.
Requirements are standard for Master's programs across Social Sciences and Humanities at Umeå. English 6 proficiency is the general rule.