Project thumbnail image
College of Engineering Unit: 
Electrical Engineering and Computer Science
Project Team Member(s): 
Samson Mont, Markus Bauer, Nour Rahal-Arabi, Madelyn Smith and Jinshui Wang
Physical Location at Expo: 
Community Plaza
Project ID: 
Project Description: 

Creating models to understand species abundance is a significant area of research in the field of Ecology. Researchers must gain a deep and comprehensive understanding of population dynamics to explain interactions between predators and prey as well as predict population abundance over space and time.
Historically, ecological researchers have used statistical methods which rely on fitting a “correct” model to data by estimating parameters that are assumed to be significant. However, symbolic regression is a promising new method for producing descriptive models because it has the potential to derive the multiple significant factors and predator-prey interactions directly from species abundance data. In addition, symbolic regression does not assume a prior model which suggests that the one it extracts is the data’s “true” model.

Project Communication Piece(s): 
PDF icon scope_and_vision_paper.pdf266.14 KB
PDF icon 2022.expoposter.cs_.035.pdf464.05 KB