Gota Morota

I am a quantitative geneticist interested in incorporating statistics, machine learning, bioinformatics, and high-throughput phenotyping data to the study of animal and plant genetics in the omics era. The core line of my research is connecting the theory of statistical quantitative genetics to currently available molecular information. I am particularly interested in statistical methods for prediction of complex traits using whole-genome molecular markers. Because phenotypic data collection is paramount in quantitative genetics, I integrate precision agriculture and high-throughput phenotyping into my research program to collect a wide range of phenotypes.

• ISE Senior Symposium 2022 Advisory Board Award, Grado Department of Industrial and Systems Engineering, Virginia Tech

• Ph.D., Animal Sciences, University of Wisconsin-Madison, Madison, Wisconsin USA, August 2014
• M.S., Dairy Science, University of Wisconsin-Madison, Madison, Wisconsin USA, December 2011
• B.S., Agricultural Science, Obihiro University of Agriculture and Veterinary Medicine, Obihiro, Hokkaido Japan, , March 2008