14 College Farm Rd
ENR Building, 1st floor
New Brunswick, NJ 08901

Curriculum Vitae

Current Positions
PhD candidate, Dept. of Ecology, Evolution and Natural Resources, Rutgers University

Degrees Held
B.S. in Computer Science
Rutgers University - Camden, 2009

Brad Greening

Graduate Student

I am interested in the application of mathematical and computational models to biological and social systems. I have found that my background in theoretical computer science provides me with many useful tools to study many interesting questions in the fields of behavioral ecology and evolutionary sociobiology.

I'm currently working primarily on my dissertation on "Higher-Order Analysis of Information Capacity and Learning Potential in Social Animal Groups"


Below are short descriptions of some of a few previous projects in various stages of completion:

  1. In our most recent project we are studying the implications of social structure and neighborly influence on the dynamic of collective decision making in social animal populations. Examining the processes that culminate in the decision of a social group forces us to understand not only what constitutes when a “decision” has been made, but what input each individual member has into that decision. Not all individuals play the same role in a social group, and as a result each may hold similarly distinctive roles in the process of arriving at a group decision. Furthermore, that each individual’s decision may be influenced by the information provided by their social contacts adds an extra layer of feedback into the dynamics of reaching the group-level decision. This opens up many fascinating questions in terms of the evolutionary origins and adaptive significance of social structure and collective decision making strategies in social animal populations.
  2. We have also been working with a collaborator in the Centers for Disease Control and Prevention to model public health responses to crisis events in urban centers, specifically in the case of an extreme heat event or an epidemic of infectious disease. In such cases, it is possible for the city to have a spike in individuals seeking medical treatment such that the existing facilities are inadequate to handle all cases. One response of public health officials would be to convert public buildings such as schools, libraries, or sports stadia for use as temporary medical facilities to supply treatment to the overflow. We employ individual-based modeling to examine which facilities would be the best options for such conversions, as well as how to route the population in such a way as to minimize loss of life.


Selected Presentations: