Observation

Estes Fund Grants Aim to Raise Awareness of Computational Tools

The William K. and Katherine W. Estes Fund, which was created to honor the legacy of influential psychological scientist Bill Estes, has awarded three grants for programs focused on increasing awareness of how computational tools, models, and data collection can improve all areas of psychological science. Overseen jointly by APS and the Psychonomic Society, the Fund supports summer schools and workshops offering training in mathematical and computational modeling for PhD students, postdocs, and advanced researchers. It also promotes the teaching and practice of rigorous methodology in experimental and quantitative psychological science.

The 2017 funded programs are:

  • “Computational Tools for Developing and Testing Models of Quantum Cognition,” a workshop organized by Jerome Busemeyer, APS Fellow Tim Pleskac, Emmanuel Pothos, Jennifer S. Trueblood, and Zheng Wang. This workshop will highlight a novel approach to constructing computational models of cognition and decision-making using quantum theory. It took place on July 21, 2017, at the University of Warwick, United Kingdom.
  • “Model-Based Cognitive Neuroscience Summer School,” a 5-day summer school program organized by Birte Forstmann, Dora Matzke, Uta Noppeney, Andrew Heathcote, Brandon Turner, Gilles de Hollander, and Guy Hawkins. Funding for this project will help raise awareness of nascent studies at the intersection of cognitive modeling and cognitive neuroscience. It occurred from July 31–August 4 in Amsterdam.
  • “Data on the Mind: Collecting, Analyzing, and Sharing Research Using Big Data and Naturally Occurring Datasets,” a 3-day workshop hosted by the Center for Data on the Mind (CDM) and organized by APS Fellow Thomas L. Griffiths, Alexandra Paxton, Michael C. Frank, and Todd Gureckis. The aim of the workshop is to encourage graduate students and postdocs to delve into the connections between cognitive science and Big Data. The entire workshop, held June 26–29, 2017, at the University of California, Berkeley, is freely and permanently available via YouTube, GitHub, and Docker. Click here for more information.