Speaker: Dr. Jeffrey Cohn

Abstract: To uncover mechanisms in psychopathology, evaluate treatment response, and offer timely feedback to clinicians, reliable, valid, efficient measures are essential. Self-report and clinical interviews, the current gold standard for diagnosis and clinical trial endpoint measurement, assess severity but are subjective, hard to standardize within and across settings, impose patient burden, and lack granularity and immediacy. Affective computing offers an increasingly powerful alternative to these methods. I present my interdisciplinary team's efforts to develop and apply objective, reliable, valid, efficient, and interpretable multimodal measures of disorder and treatment response.

Bio: Dr. Jeffrey Cohn is professor emeritus of Psychology and Intelligent Systems at the University of Pittsburgh, courtesy faculty at the Robotics Institute of Carnegie Mellon University, chief scientist at Deliberate AI, and scientific advisor at Realeyes and Embodied. For the past 40 years, his research has been supported by the U.S. National Institutes of Health, among other U.S. agencies.

Website: https://jeffcohn.net