Mark Himmelstein, Georgia Institute of Technology
Measuring Persuasion Without Measuring a Prior Belief: A New Application of Planned Missing Data Techniques
2025 Dissertation Prize
About the speaker
Mark Himmelstein received his Ph.D. in Psychometrics and Quantitative Psychology at Fordham University. After graduating, he joined Georgia Tech as an Assistant Professor of Psychology where he teaches courses in statistics and manages the Subjective Uncertainty and Belief lab. His research lies at the intersection of human judgment and decision-making, normative models of decision theory, and quantitative methodology. His work has included adapting Item Response Theory models to assess the quality of probability forecasts for real world geopolitical events, developing computational models of how people update their beliefs under uncertainty, and novel implementations of planned missing data designs to facilitate counterfactual inference.