James is currently a Ph.D. candidate and is supervised by Dr. Zhiwu Zhang at Washington State University. With a Bachelor degree in agronomy and a strong background in computational biology, his research mainly centers on developing state-of-art statistical approaches to solve problems in practical breeding programs. To accelerate the breeding process and to enable breeders to apply profound statistical analyses in their research, a user-friendly software, iPat (zzlab.net/iPat), was developed and has been published on Bioinformatics as my first publication in 2018. Without any programming skill or knowledge, breeders can use iPat to efficiently implement several types of genomics studies and methods which originally were only available under command-line interfaces. Besides, James also work on introducing the artificial neural network (ANN) approaches to the fields of functional genomics studies, since ANN has strong capabilities of capturing non-linear variation that is limited addressed by most current methods. His preliminary studies have shown its promising application on predicting the wheat falling number and this finding is expected to save considerable loss from wheat production in Washington.