My current research focuses on building deep integrations of AI tools into behavioral science research workflows to accelerate the pace of scientific discovery. My work applies computational approaches to automate and enhance scientific research tasks—from hypothesis generation and experimental design to data analysis and theory development.
My background includes a doctorate in marketing from the MIT Sloan School of Management, postdoctoral research at Princeton University's School of Public and International Affairs, and an undergraduate foundation in neuroscience from the University of California, Berkeley. I am currently Assistant Professor of Marketing and David Eccles Emerging Scholar at the Eccles School of Business, University of Utah.
AI-Powered Research Automation
Developing tools that harness AI models to automate key steps in the behavioral science research process.
Preference Elicitation
Applying behavioral theory and language models to develop rich understanding of individual user preferences.
Selected Publications
Algorithms propagate gender bias in the marketplace—with consumers' cooperation
Journal of Consumer Psychology
Algorithm overdependence: how the use of algorithmic recommendation systems can increase risks to consumer well-being
Journal of Public Policy & Marketing