Zakia Hammal

Zakia Hammal is an Assistant Research Professor jointly appointed in the Robotics Institute, Biomedical Engineering, and the Machine Learning Department at Carnegie Mellon University. Her research focuses on multimodal human behavior modeling, affective computing, and machine learning for health-related applications. Hammal develops computational methods that analyze facial expressions, vocal cues, and body movement dynamics to better understand social interaction and psychological states. Much of her recent work addresses automated assessment in clinical and therapeutic contexts, including models for evaluating depression severity, measuring pain intensity, assessing expressiveness in children with facial abnormalities, and analyzing non-verbal communication in mother–infant interactions or autism spectrum disorder. Supported extensively by NIH funding, her work spans both foundational research and real-world deployment. She has held numerous leadership roles in ACM ICMI, IEEE FG, and ACII communities, serving as an editor, chair, and organizer for major conferences and workshops. Hammal’s contributions lie in bridging behavioral science, machine learning, and human-centered robotics to improve wellbeing and human–AI interaction.