Depression is a leading cause of disability worldwide. Effective, evidence-based treatments for depression exist but many individuals suffering from depression go undetected and therefore untreated. Efforts to increase the accuracy, efficiency, and adoption of depression screening thus have the potential to minimize human suffering and even save lives. Recent advances in computer sensing technologies provide exciting new opportunities to improve depression screening, especially in terms of their objectivity, scalability, and accessibility. Professor Morency and Dr. Szigethy are collaborating to develop sensing technologies to automatically measure subtle changes in individuals’ behavior that are related to affective, cognitive, and psychosocial functioning. Their goal is to develop and refine computational tools that automatically measure depression-related behavioral biomarkers and to evaluate the clinical utility of these measurements.