Goo Jun received his Ph.D. degree in Electrical and Computer Engineering from the University of Texas at Austin, M.S. degree from the University of Michigan at Ann Arbor, and B.S. degree from KAIST, South Korea, respectively. He completed his post-doctoral training at the Center for Statistical Genetics, University of Michigan at Ann Arbor in 2014. He is currently an Assistant Professor at Human Genetics Center, UTHealth School of Public Health. He has worked on machine learning, image processing, and remote sensing. Since his post-doctoral training, he has been working on statistical genetics, computational biology, bioinformatics, and sequence data analysis. His research is focused on development of computational and statistical methods for analysis of massive data to understand genetics and biology of complex traits. He has been working on the analysis of large-scale next-generation sequencing data, for which he developed statistical models and software pipelines for detecting sample contamination, variant discovery, machine-learning based variant filtering, and genotyping of structural variations. These tools have been used as one of the main software pipelines in many large-scale sequencing projects including the 1000 Genomes Project. Dr. Goo Jun is currently serving as an academic editor at PeerJ.