Jay I. Myung

This researcher develops mathematical and computational methods for building, testing, and comparing models of human decision-making and cognition, including tools for designing experiments that most efficiently distinguish between competing theories. Work spans adaptive experimental design, Bayesian statistics, and model comparison techniques, with applications ranging from psychiatric research (e.g., decision-making in obsessive-compulsive disorder) to vision science and even materials science optimization. Much of the output includes freely available software tools (like the ADOpy Python package) intended for use by other researchers.

Publication output rose to a peak around 2019-2020 (8 papers each year) but has since been lower and more variable, averaging under two papers per year over the last five years, with a recent uptick in 2025.

Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026