Stevens’ research spans the computational and computer sciences from high-performance computing, to the building of innovative tools and techniques for biological science and infectious disease research as well approaches to advance deep learning to accelerate cancer research. He also specializes in high-performance computing, collaborative visualization technology, and grid computing. Currently, he is the PI of the Bacterial / Viral Bioinformatics Resource Center (BV-BRC) which is developing comparative analysis tools for infectious disease research and serves a large user community; the Exascale Deep Learning and Simulation Enabled Precision Medicine for Cancer project through the Exascale Computing Project (ECP), which focuses on building a scalable deep neural network application called the CANcer Distributed Learning Environment (CANDLE); the Predictive Modeling for Pre-Clinical Screening (Pilot 1) of the DOE-NCI Joint Design of Advanced Computing Solutions for Cancer (JDACS4C) project; and the Co-design of Advanced Artificial Intelligence (AI) Systems project focused on predicting behavior of complex systems using multimodal datasets.