Research Framework

WHAT WE STUDY Affective and Interpersonal Communication COMMUNICATIVE BEHAVIOR Verbal Behavior Syntax Semantics Discourse Nonverbal Behavior Facial expression Vocal behavior Gesture and motion SOCIAL INTERACTION Interpersonal Dynamics Change Regulation Influence Social Perception Cultural context Relational context Situational context MENTAL HEALTH Clinical Assessment Symptoms Diagnosis Flourishing Clinical Mechanisms Treatment process Outcomes Health behavior RESEARCH METHODOLOGY Statistical Modeling Bayesian estimation · Multilevel modeling · Simulation Research Practice Measure validation · Reproducibility · Tutorials COMPUTATIONAL TOOLS Artificial Intelligence Behavior sensing · Machine learning · Language models Open Resources Research software · Research databases · Education resources

Substantive Areas

Our substantive work asks how people communicate emotion and relate to one another, and what this means for mental health. It spans three areas. In studying communicative behavior, we investigate verbal behavior (syntax, semantics, and discourse) and nonverbal behavior (facial expression, vocal behavior, and gesture and body motion). In studying social interaction, we investigate interpersonal dynamics (change over time, regulation, and how people influence one another) and social perception (how people read one another, and how cultural, relational, and situational context shapes what they see). In studying mental health, we investigate clinical assessment (symptoms, diagnosis, and flourishing) and clinical mechanisms (treatment process, outcomes, and health behavior).

Methodological Foundation

Supporting these areas is a wide foundation of interdisciplinary methods. Research methodology covers statistical modeling (Bayesian estimation, multilevel modeling, and simulation) and research practice (measure validation, reproducibility, and tutorials). Computational tools cover artificial intelligence (behavior sensing through computer vision, signal processing, and natural language processing; machine learning; and large language models) and open resources (research software, research databases, and education resources).

Research Funding

Current Funding

R34 Developing and Evaluating a Firefighter Self-Administered Neurostimulation Intervention for Traumatic Stress to Reduce Alcohol Use

National Institutes of Health (NIAAA) 05/2026 – 04/2029Sprunger (PI), Co-I: Girard

DoD Assessment of Eating Disorder and Comorbidity Risk and Resilience in Recent Military Enlistees

Department of Defense 04/2025 – 03/2027Forbush (PI), Co-I: Girard

R34 Building Healthy Eating and Self-Esteem Together for University Students (BEST-U): A Pilot Randomized Controlled Trial of an mHealth Intervention for Binge-Spectrum Disorders

National Institutes of Health (NIMH) 01/2025 – 12/2027Forbush, Christensen-Pacella (PIs), Co-I: Girard

P20 COBRE Computational Assessment of Communicative Behaviors in Posttraumatic Stress

National Institutes of Health (COBRE) 01/2025 – 12/2026Girard (PI)

Completed Funding

R01 Context-Adaptive Multimodal Informatics for Psychiatric Discharge Planning

National Institutes of Health (NIMH) 04/2021 – 02/2025Baker (PI), Co-Is: Girard, Morency

NSF Kansas Data Science Training Pathways | An Integrated Model

National Science Foundation (EPSCoR REI) 01/2024 – 12/2024Girard (PI)

Google Novel Scalable Mental Health Screening Procedures on Ubiquitous Sensing Devices

Googler-Initiated Grant 11/2022Girard (PI)

R21 Multimodal Dynamics of Parent-Child Interactions and Suicide Risk

National Institutes of Health (NIMH) 09/2022 – 07/2023Burke (PI), Co-Is: Girard, Li, Morency

PHDA Towards Automated Multimodal Behavioral Screening for Depression

Pittsburgh Health Data Alliance (CMLH) 03/2019 – 02/2021Morency (PI), Co-I: Girard

NSF Dyadic Behavior Informatics for Psychotherapy Process and Outcome

National Science Foundation (IIS, SCH) 09/2020 – 08/2022Cohn, Morency, Swartz (PIs), Co-Is: Bylsma, Fournier, Girard