Owen Queen explores robust and interpretable artificial intelligence for healthcare and biomedicine. Queen's research concentrates on elucidating the behaviors of high-performance deep learning models through explainable artificial intelligence (XAI), with a focus on graph and sequential models. He also works in protein representation learning, training large-scale, multitask models that can be used for a variety of downstream tasks in therapeutics. He received his B.S. in computer science and mathematics from the University of Tennessee, Knoxville, and he has previously worked on projects spanning multiple applications of computation and machine learning in the natural and social sciences. He is also an alumnus of the 2021 DBMI Summer Institute of Biomedical Informatics.