Gregory Francis

Areas of Expertise

• Computational models of perception, especially dynamic vision, and their application to human factors design problems.
• Experimental methods and publication bias.

Department of Psychological Sciences Research Area(s)

• Cognitive Psychology
• Mathematical and Computational Psychology

Biography

My laboratory focuses on three main topics. First, I study neural network models of human behavior. I have studied the dynamic characteristics of a neural network model of visual perception and, through computer simulation, demonstrated that the model’s behavior matches human data on dynamic vision. The model properties are now being further examined to explain additional human data. Additional research investigates the dynamic properties of recurrent networks for pattern recognition and memory.

I’ve made available an on-line set of simulations for models of backward masking. These simulations allow anyone to use the models without having to write their own code.

Second, I explore human-computer interactions. Computer information is often presented in a menu format where a user moves through a sequence of menus to reach desired information (think of an ATM money machine). My research has identified a quantitative method for organizing these types of menus so that they are easy to use. Currently, these methods are organized in MFDTool, a software aid for the design of multifunction displays. Much of this research has been supported by the U.S. Army Aeromedical Research Laboratory at Ft. Rucker, AL.

Finally, I am involved in the creation of a novel set of teaching tools. The Cogntive Psychology Online Laboratory provides a set of java program that allow a user to explore some online demonstrations of experiments in cognitive psychology. A similar project called the Visual Perception Online Laboratory is dedicated to experiments related to vision.

Recruiting graduate students for Fall 2025 admission.

Education

• PhD, 1993, Boston University

Websites

• Francis Lab

Current Courses

• PSY 20000 - Introduction to Cognitive Psychology
• PSY 20100 - Introduction to Statistics in Psychology
• PSY 62601 - Bayesian Statistics for Psychological Sciences