Where Computer Science Meets Public Health: Causal Discovery
Our primary mission is to promote transparency, rigor, and open communication in discovering causal diagrams. We are actively applying these models to critical areas like health research, nutrition, and fairness in care delivery.
Health Datasets
Identifying causal relationships in complex health data.
Causal Graphs
Constructing causal models synthesized from existing literature.
Nutrition Policy
Informing and refining public nutrition policy.
Healthcare Disparities
Reducing systemic inequities across healthcare delivery.
Drug Safety
Enhancing post-market surveillance and safety detection.
Patient Care
Personalizing precision clinical decisions.
Looking Ahead: Year One Objectives
In our first year, we will focus on laying the groundwork to establish an internationally recognized, sustainable hub. We will be organizing two foundational workshops to shape the research agenda and forge collaborative partnerships.