Richard A. Hullinger
Department of Psychological and Brain Sciences
Indiana University, 1101 E. 10th St., Bloomington, IN 47405
Office: (812) 856-6854
Email: rahullin{AT}indiana{DOT}edu
Updated January, 2013
printable (.pdf) version


Education

Ph.D. in Psychological and Brain Sciences and Cognitive Science, 2011
Indiana University, Bloomington, Indiana
Advisor: John K. Kruschke
Thesis Title: An Evolutionary Analysis of Selective Attention

B.S. in Physics, 1996
B.S. in Computer Science, 1996
Magna Cum Laude
Rensselaer Polytechnic Institute, Troy, NY

Honors and Fellowships

Teaching Experience

Visiting Assistant Professor, Indiana University:
K300 Statistical Techniques, Spring 2012 — Spring 2013
Q301 Brain and Cognition, Spring 2013
P335 Cognitive Psychology, Fall 2011 & 2012
C105 Brains & Minds, Robots & Computers, Fall 2011 & 2012
P199 Carrers in Psychology, Spring 2012 & 2013
P102 Introductory Psychology, Fall 2011

Instructor, DePauw University:
PSY100 Introductory Psychology, Spring 2010

Associate Instructor, Indiana University:
E104 Brains & Minds, Robots & Computers, Fall 2010
K300 Statistical Techniques, Spring 2009 – Spring 2010

Laboratory Instructor, Indiana University:
P211 Research Methods in Psychology, Fall 2006 – Spring 2008

Research Interests

       My research interests encompass a range of cognitive science topics with a primary focus on evolutionary simulations of attention and learning. I use simulated evolution as a means to investigate the types of environmental information structures that lead to the emergence of attention as an adaptive mechanism. I employ genetic algorithms to evolve simple connectionist networks in a range of environments. These environments may vary in terms of the underlying structure of the cues and responses, the temporal structure, or the amount of noise that is present in the environment. I then analyze the evolved agents to determine if they show signs of attentional behavior.
       The goal of my work is to explain attentional behaviors as adaptive, evolved responses that can only be fully understood in the context of the environments that gave rise to them.

Publications

Kruschke, J.K., & Hullinger, R.H. (2010). Evolution of attention in learning. In: N. Schmajuk (Ed.), Computational Models of Classical Conditioning, pp. 10 - 52. Cambridge University Press.

Presentations

Professional Experience

Patents

 “System for Analyzing Television Programs,” U.S. Patent Number 6,295,092, issued Sept. 25, 2001. Inventors: R. Hullinger et al