Samuel Baltz, PhD, Massachusetts Institute of Technology, USA
Samuel Baltz is the Research Director of the MIT Election Data and Science Lab. Samuel is an election scientist who uses computational social science to study the interaction between voter behaviour and election rules. Samuel holds a PhD in political science and scientific computing and an MS in mathematics from the University of Michigan, and a BS in astrophysics and political science from the University of Toronto.
Soubhik Barari, PhD, NORC at the University of Chicago, USA
Soubhik Barari is a Research Methodologist in the Department of Methodology and Quantitative Social Sciences, National Opinion Research Center (NORC) at the University of Chicago. His methodological areas of expertise include data science, survey methodology, and causal inference while substantive areas of interest include media, public opinion, and elections.
Jose M. Pavía, PhD, Universitat de Valencia, Spain
Jose M. Pavía, MSc in Maths and PhD in Economics and Business Science, is a Quantitative Methods Professor and director of the Elections and Public Opinion Research Group of the Universitat de Valencia. Pavía develops and applies statistical and machine learning methods in many areas of social sciences. With broad and varied research interests, his work focuses on the search for innovations that bridge the gap between theory and practical applications and include issues related to, among others, electoral processes, prediction, statistical (machine) learning, ecological inference, crime detection, survey research, sampling or public opinion.