Is a Computational Genomics Specialist with Medical Science & Computing and a contractor with the Bioinformatics and Computational Biosciences Branch in the Office of Cyber Infrastructure and Computational Biology at the National Institute of Allergy and Infectious Diseases. His main research interest is on using machine learning to improve our understanding of genomic and proteomic data. His graduate work at George Mason University focused on the computational prediction of antimicrobial peptides and he has recently applied deep learning to build state-of-the-art classification models. His postdoctoral work at the U.S. Department of Agriculture developed novel computational methods to compare genomes and identify gene targets useful for detecting fungal plant pathogens.