Jun Yan is a Professor in the Department of Statistics at the University of Connecticut. He earned his Ph.D. in Statistics from the University of Wisconsin in 2003. His research spans several areas of statistics including network analytics, spatial extremes, survival analysis, multivariate dependence, and clustered data analysis, with a notable emphasis on statistical computing. His work has significant applications across various domains, such as public health, finance, sports, and the environment. A foundational element of his career, his passion for statistical computing and software development epitomizes his dedication to connecting the theoretical underpinnings with practical applications. Beyond his research, he enjoys teaching, taking pride in nurturing the next generation of data scientists and expanding his academic pedigree. He has been the Editor of the Journal of Data Science since 2020.
Books
- Marius Hofert, Ivan Kojaninovic, Martin Machler, and Jun Yan (2018): Elements of Copula Modeling with R | R companion
- Dipak Dey and Jun Yan (Eds) (2015): Extreme Value Modeling and Risk Analysis: Methods and Applications | Code Supplement