Brandon Kramer, Ph.D.

Social Scientist / Data Scientist

Brandon Kramer, Ph.D. is a Postdoctoral Research Associate in the Social and Decision Analytics Division at the University of Virginia’s Biocomplexity Institute. Generally, I am interested in researching issues related to ethics and inequality at the intersection of science, technology, politics, and health. While formally trained as a sociologist, I use aspects of computational social science and science & technology studies to address a range of social and policy concerns. My work has been published in the Annual Review of Nutrition, Science, Technology & Human Values, BioSocieties, and Annals of Behavioral Medicine.

Dissertation Research

In my dissertation project (Rutgers University, 2019), I studied how testosterone has been used to racialize populations in biomedical research and the impact that this has on understanding health disparities. By integrating various computational and qualitative strategies, I traced how testosterone researchers advance misleading and dangerous claims about racial differences in health and behavior, ultimately arguing that these discourses contribute to racially-specific healthcare practices that exacerbate prostate cancer disparities between white and black men. As part of this ongoing research, I am developing a project that uses natural language processing, machine learning, and network analysis to study diversity in biomedical research more broadly.

Collaborative Research

In my present role at the UVA Biocomplexity Institute, I spend most of his time working in a multidisciplinary team science environment. Since graduating, Brandon has worked on collaborative projects - both in and outside of UVA - that examine international collaboration networks in open-source software development, the political history of nutrition science, the rise of “diversity” in biomedical research, the use of predictive modeling to evaluate risk of gentrification and emerging employment areas, and a project investing how built infrastructure shapes economic mobility across three states. I have experience in network/graph analysis, natural language processing, regression, probabalistic record linkage, data visualization, geospatial mapping, survey design and implementation, as well as a number of qualitative strategies like content/discourse analysis and interviewing.

Before moving to Biocomplexity, I collaborated with several research groups in graduate school. Using an experimental framework, my colleagues Kristen Springer (Rutgers), Mary Himmelstein (Kent State) and I studied how masculinity threats impact young men’s biological stress reactivity as well as the impact that this may have gendered disparities in health outcomes. During this project, I became interested in how scientific practices and technologies shape biomedical knowledge production. To supplement this biosocial training, I worked under Guggenheim fellows Rebecca Jordan-Young (Barnard) and Katrina Karkazis (Amherst), getting exposure to qualitative methods like interviews and content analysis as well as feminist and critical race frameworks, while contributing as a research fellow for their National Science Foundation-funded book project on testosterone.

Shortly after this, I collaborated on a William T. Grant-supported project working with Matthew Weber (Minnesota) and Itzhak Yanovitzky (Rutgers) on a project that applied statistical and inferential social network analysis to examine policymakers’ use of evidence in the context of childhood obesity legislation. Finally, I served as a research fellow on a National Institute of Drug Abuse-funded project with Kathryn Greene (Rutgers) and Michael Hecht (Real Prevention LLC) testing an interactive technology-based substance use intervention. Overall, this breadth of work shows that I can draw on a range of qualitative and computational tools to address research questions at the intersection of science, technology, policy, and health. You can find links to my past work in the projects tab or check out his coding on GitHub.