Multimodal Machine Learning for supporting attachment-based intervention
Collaborating with Dr. Lisa Berlin‘s team at the University of Baltimore School of Socia Work, we are exploring the feasibility of automating the process of characterizing the parent-child interaction using video data collected at home from the Attachment-based intervention. We are experimenting with a suite of multimodal machine learning analysis methods. This project lays the foundation for future research in developing data-driven and human-centered tools to support social workers in delivering home-based interventions.
Collaborator: Dr. Lisa Berlin and her teams (Unversity of Maryland School of Social Work)
- Atefeh Jebeli (UMBC IS Master student, Spring 2022 – present)
- Sophia Papparotto (UMBC CS Undergraduate student, Spring 2022 – present)