I'm an Assistant Professor of Computer Science at St. Bonaventure University. I earned my PhD in Technology, Media & Society from the University of Colorado Boulder, where I worked closely with the the Department of Information Science in the Philanthropic Informatics Research Lab.Current Work
I conduct empirical research in human-computer interaction and computer supported cooperative work, with a focus on philanthropic informatics. I work with human and social services organizations to conduct research in the areas outlined in the research interests section.Previous Work
I earned a B.S. from RIT's College of Computing and Information Sciences and a M.S. from the University of Colorado's College of Engineering and Applied Science. I've worked as a professional in the nonprofit, data science, and computer security spaces. More information on my background can be found in my LinkedIn profile, and CV.
My research focuses on several themes of big data work in the nonprofit sector, specifically human and social service organizations. Empirical work that explores these themes can be found below in the publications section. My research questions most often dictate the application of a variety of qualitative methods including interviews, observations, data journey maps, and discourse analysis.
Who is included or excluded in the drive to use big data in the nonprofit sector? What can big data represent or not represent about nonprofit work? How does big data deal with the complexity of social systems which resist quantification and systematization?
Big data incorporates a belief that it can unlock access to new insights through a higher form of intelligence. How does this mythology affect the adoption of big data in human and social services organizations? How does this mythology shape evidence-based practices, and what are the implications for organizations and clients?
How do power dynamics influence representations or exclude individuals? How do power dynamics work to shape big data infrastructure? What are the implications of this influence?
When public policy makers ask for data about social issues, what aggregated data do they ask for, or not ask for? How do they deal with ambiguity and uncertainty in big data?
Big data in the nonprofit sector is most likely to result from aggregation across organizations. How do organizations use data in working together at the community level to address social issues? What barriers to leveraging big data are encountered, particularly in terms of stigmatized domains?
What are responsible ways for researchers to engage with nonprofits given the importance of their work, and the limited human and financial resources available to them? How can researchers contribute meaningfully to our nonprofit partners?