Gizem Korkmaz, Ph.D. Email and Phone Number

I am a PhD-level economist experienced in data science and conducting social, behavioral, and policy research. The hallmark of my research is to leverage my background in traditional economics (e.g., applied game theory, behavioral economics), and to blend it with new tools and methods from data science such as machine learning, natural language processing, and social network analysis. In developing innovative methods to address questions raised by policymakers and/or communities, I’ve leveraged traditional and novel data sources including administrative records (e.g., 911 calls, education and workforce data, patient records), unstructured text-based data scraped from the web, such as social media, to ask how we can make data useful for people and communities. I’ve worked on a broad range of topics, from public safety, R&D innovation, education and workforce, science policy. I led various projects in partnership with local, state, and federal government stakeholders and industry sponsors to solve real world problems. Previously, I worked as a Research Associate Professor at UVA’s Biocomplexity Institute, and I was also the Co-director of UVA’s Data Science for the Public Good program. In this role, I participated in the management and strategic direction of the organizations as a member of the Senior Leadership. Managing teams of junior researchers and higher-ranked coworkers have been my strong suits throughout my career. I was selected as the 2016 Outstanding New Faculty by Virginia Tech Northern Capital Region Faculty Association.Expertise in program development, research design, modeling and data analysis using computational and statistical methods with proven track record. Proficient in R, SQL, Git, Gephi, LaTeX, and working in high-performance computing environments. Strong communication, writing, organizational, and project management skills in fast-pace transdisciplinary team environments.Research Interests: policy research, data science, data reusability, social and economic networks (mathematical and computational modeling, and empirical analysis), science of science, open source software innovation, social contagion, collective action