Professor Nephew’s work is broadly focused on identifying and studying neurobehavioral mechanisms of mental illness and developing effective interventions. Research areas include mindfulness-based stress reduction to develop machine learning-based early predictors of severe depression and suicidality; postpartum depression/anxiety, and the impact of social stress, alcohol, and air pollution on behavior, immune factors, neural connectivity, neuroendocrinology, and related epigenetic changes.

His research also leverages machine learning to detect anatomical changes in the brain, with the goal of accurately predicting Alzheimer's disease, to allow for earlier diagnosis. He is also part of a research team working to identify predictors to determine who responds well to mindfulness interventions for chronic low back pain.