Ph.D. in Statistics (Minor in Computer Sciences), University of Wisconsin-Madison
M.A. in Statistics, University of California, Berkeley
B.S. in Mathematics, Seoul National University, Korea
Research Interests: Biostatistics; Survival Analysis, Machine Learning
Hongshik Ahn’s specialty is tree-structured regression modeling for censored survival data, classification of high-dimensional data, and machine learning. After earning his Ph.D., he initially worked as Mathematical Statistician at the National Center for Toxicological Research (NCTR) on animal carcinogenicity, developmental toxicology, and drug stability analysis. He came to Stony Brook in 1996. He continued working on NCTR problems while developing collaborations with Stony Brook biomedical researchers and researchers in New York University and Mount Sinai Medical School
My current research area is classification based on ensembles of classifiers for high-dimensional data. A robust classification procedure is developed based on ensembles of classifiers, with each classifier constructed from a different set of predictors determined by a random partition of the entire set of predictors. A primary area of application is the classification of subjects into cancer-risk or cancer-type categories based on high-dimensional biomedical data. The methods can be used to improve class prediction in many other areas of application involving high-dimensional prediction sets.