Daniel Benjamin

Daniel Benjamin is an Assistant Professor of Decision Sciences at Nova Southeastern University's H. Wayne Huizenga College of Business & Entrepreneurship. His research explores how complexity influences judgment and decision-making, particularly in interactions with model outputs and technology, applied to policy-relevant domains such as geopolitical prediction, meta-research in social and biomedical sciences, climate change perception, and expert forecasting.

Education:

• Ph.D. in Psychometrics and Quantitative Psychology, Fordham University
• M.A. in Psychology, Fordham University
• B.A. in Mathematics and Psychology, University of North Carolina at Chapel Hill

Dr. Benjamin's work focuses on quantifying human biases in forecasting, evaluating reproducibility in preclinical research, and analyzing machine influence on human judgment. His recent publications examine clinical trial prediction accuracy, hybrid geopolitical forecasting models, and knowledge graph applications in scientific evaluation.

Scientific Awards:

• NPR coverage for "Can cancer researchers accurately judge whether preclinical reports will reproduce?"
• Nature coverage for "Can cancer researchers accurately judge whether preclinical reports will reproduce?"
• PLoS Biology Top Media Hits of 2018

At NSU, he teaches QNT 5000 Foundations of Business Statistics and QNT 5160 Analytical Modeling for Decision Making. His research has been funded by DARPA, IARPA, NSF, CIHR, Genome Canada, and BioCanRx.