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Richard GonzalezRichard Gonzalez

Center Director, Research Center for Group Dynamics, Institute for Social Research
Co-Director, BioSocial Methods Collaborative
Amos N Tversky Collegiate Professor, Psychology and Statistics, LSA
Professor of Integrative Systems and Design, College of Engineering


E-mail: Email Richard Gonzalez
Address: Research Center for Group Dynamics
Institute for Social Research
University of Michigan
426 Thompson Street
Ann Arbor, Michigan 48106
Phone: 734-647-6785

Richard Gonzalez

About Me

I received my PhD in 1990 from Stanford University in Psychology. I worked with Phoebe Ellsworth studying psychology and law and with Amos Tversky studying mathematical modeling and judgment and decision making. I spent seven years at the University of Washington’s Psychology department, a sabbatical year at Princeton University, and have been at the University of Michigan’s Psychology department since 1997. More about me >>


My research interests focus on judgment and decision making (JDM). Given that so many topics in psychology are related to JDM it makes it look as though I work on many different topics. Actually, I see a simple theme across all my research. I am interested in how people make judgments and what influences their decisions and choices. More about Research >>


I’ve been fortunate to work with amazing colleagues, coauthors, collaborators, and students throughout my career. Read about People >>


  • Theories of Social Psychology
  • General Linear Modeling Course
  • Multivariate Statistics
  • Generalized Linear Modeling Course
  • Structural Equations Modeling Course
  • Statistics Animation Page
  • Design Science PhD Program

More about Teaching >>

Recent Posts

Cardiovascular health and daily stress among White and Black Americans

Daily stress and cardiovascular reactivity may be important mechanisms linking cumulative life event stress with cardiovascular health and may help to explain racial health disparities. This study assessed links between trajectories of life event stress exposure, daily stressors, and cardiovascular reactivity among Black and White individuals.

Estimating a typical path from GPS data

Finding insights from sensor data such as GPS can be tricky. Commuting between home and work may not always follow the same path as some days there are additional stops for errands or alternate routes taken. We propose an algorithm for extracting a typical path from a collection of trips coded by GPS coordinates.