I’m a computational and mathematical sociologist studying inequality in global scientific knowledge production and diffusion. In my work, I use a variety of techniques, including natural language processing, social network analysis, survey experiments, simulations, and interviews, to study hierarchies, complexity, and diversity. My work has been featured in Nature Human Behaviour, Nature Communications, Research Policy, Social Networks, Journal of Informetrics, and Sociological Science. I’m an associate professor at the University of Arizona’s School of Sociology. I am also affiliated with the College of Information Science and the Applied Math Graduate Interdisciplinary Program (GIDP). I am the founder and director of the Global Knowledge Lab and Observatory (i.e., The Global Lab). I’m the recipient of a National Science Foundation (NSF) CAREER Award (2024-2029) to study how international politics shapes the field of artificial intelligence (AI) and its researchers. I have received over a million dollars in grants as the PI or co-PI. Prior to Arizona, I was an assistant professor at the City University of New York, Queens College’s Department of Sociology. I was also a lecturer and data science postdoctoral researcher at the University of California, Berkeley’s School of Information. I received my Ph.D. from Stanford, my master’s degrees from the Harvard Kennedy School and Columbia, and my B.Sc.Eng. from Duke.
A sociologist from the University of Arizona, Charles Gomez, has been awarded a CAREER grant from the National Science Foundation to study the impact of international politics on research in Artificial Intelligence (AI). The project examines how collaboration and competition between countries like the United States and China influence AI research, with a focus on identifying distinct national signatures in academic publications and investigating potential bias in evaluating research from different countries.
Key aspects of the grant:
- Investigates how international politics shapes the global field of AI research
- Examines variations in international collaboration and contributions to the field
- Analyzes potential bias in evaluating research from different countries
- Utilizes social network analysis, natural language processing, and survey experiments to gather data.