Jeffrey Girard

Dr. Jeffrey Girard serves as Assistant Professor and M. Erik Wright Scholar in the Psychology Department at the University of Kansas, directing the Brain, Behavior & Quantitative Science Program and co-leading the Kansas Data Science Consortium. His interdisciplinary research bridges psychology, computer science, and statistics to investigate emotional expression through verbal and nonverbal behavior, with emphasis on individual differences and social contexts.

Dr. Girard's educational background includes:

• Ph.D. in Psychology (Clinical) from the University of Pittsburgh
• M.S. in Psychology (Clinical) from the University of Pittsburgh
• B.A. in Psychology & Philosophy from the University of Washington

His research centers on affective communication and affective computing, examining how emotions manifest in interpersonal interactions across clinical and non-clinical populations. Key focus areas include transdiagnostic psychiatry, multimodal behavior analysis, and the development of computational tools for clinical assessment. This work integrates statistical modeling with machine learning to address questions in interpersonal functioning and mental health diagnostics.

Analysis of Dr. Girard's recent publications (2023-2025) reveals strong trends in computational psychiatry, with emphasis on multimodal datasets for emotion recognition, AI-driven clinical assessment tools, and transdiagnostic approaches to psychopathology. His work consistently bridges technical innovation in affective computing with real-world clinical applications, particularly in depression assessment and psychosis research.

Scientific recognition includes:

• M. Erik Wright Scholar

Dr. Girard actively contributes to academic service through editorial roles at IEEE Transactions on Affective Computing, Clinical Psychological Science, and other leading journals. He serves on executive boards for the Society for Interpersonal Theory and Research, Society for Affective Science, and Hierarchical Taxonomy of Psychopathology society, demonstrating leadership in advancing interdisciplinary research methodologies.

He directs the Affective Communication and Computing Lab, which develops computational frameworks for analyzing emotional expression in clinical contexts, and co-leads the Kansas Data Science Consortium to foster cross-departmental data science initiatives.