Explore How CoDES Faculty Collaborate with others to Drive High-Impact Research

This interactive visualization showcases the vibrant network of co-authorship among CoDES center faculty and their collaborators, with connections reflecting the number of shared publications between researchers. It illustrates the deeply collaborative and multidisciplinary nature of CoDES, which brings together experts in pharmacoepidemiology, health economics, health services research, artificial intelligence, and data science to address real-world public health challenges. The density and interconnectivity of the network highlight the productivity and reach of CoDES faculty across many domains. By joining CoDES, collaborators gain access to a thriving ecosystem of leading researchers, a robust infrastructure of healthcare data and analytical tools, and a supportive environment that values innovation, methodological advancement, and multidisciplinary collaboration.

Discover the SCOPE of CoDES Research Across Clinical Areas and Populations

This interactive visualization reveals the expansive network of research topics, disease areas, and patient populations studied by CoDES center faculty and their collaborators, with relatedness determined by the number of co-authored publications. It highlights the center’s wide-ranging expertise in areas such as pain, cardiovascular disease, and infectious disease, as well as focused work in key populations including pediatrics, older adults, and women’s health. The diversity and productivity of research evident in this network reflect CoDES’s commitment to generating real-world evidence that complements and extends insights from clinical trials—leveraging rich healthcare data to address unanswered questions in complex, understudied, and vulnerable populations. By joining CoDES, collaborators gain access to a uniquely multidisciplinary and high-performing research environment that is well-equipped to tackle complex questions at the intersection of data science, clinical research, and public health.