Published January 18, 2021
The International Chinese Statistical Association (ICSA) has named Guan Yu, PhD, Department of Biostatistics in the School of Public Health and Health Professions, as its 2020 ICSA Young Outstanding Researcher Award. The ICSA gives the award to an early-career researcher in recognition of outstanding work in statistical theory, methodology and/or applications. Yu received his award during the recent ICSA Applied Symposium.
Yu’s research is concerned with the development, evaluation and application of new statistical machine learning and high dimensional statistical inference techniques.
“Massive and complex data are prevalent in almost every aspect of modern scientific research,” Yu said. “It is vitally important to manage these huge amounts of data, and make reliable prediction and inference. Statistical machine learning and high dimensional statistical inference techniques have great flexibility in handling such data.”
Over the last few years, Yu has developed several new statistical methods for graph-guided statistical learning, block-missing multi-modality data analysis, and statistical inference for sparse penalized regression. His current research focuses on the development of new non-parametric methods with theoretical guarantees for the statistical machine learning problems in both the traditional supervised learning and the practical transfer learning settings.
Founded in 1987, the International Chinese Statistical Association (ICSA) has over 1000 active members and publishes two scientific journals: “Statistica Sinica” and “Statistics in Biosciences.” Among other aims, it promotes the theory and applications of statistical disciplines through scholarly activities, and promotes better understanding and interest by the general public in statistical methodology and related applications.