Project Overview

Facial Recognition and Genetic Tools for Harbor Seal Conservation

Faculty Sponsor

Krista Ingram (


Computer Science
Natural Sciences


We recently developed a seal facial recognition software (SEALNET) to aid in ecological and behavioral studies of harbor seals. Seals are a top predator in marine coastal ecosystems and a key ecosystem regulator. Harbor seals occupy diverse climatic zones and environments and are widely considered the most successful pinniped species. Their high dispersal ability suggests limited population structure. Still, recent genetic an tagging studies suggest significant structure in populations—an indication that there is much to be learned from careful, in-depth studies of local populations. In this project, we will improve the accuracy of our softwar as well as automate and simplify the process to improve use of the software by others. We will also conduct preliminary genetic studies by sample environmental (eDNA). Using our software and genetic analyses, we will study the behavior and population structure of a population of harbor seals in Casco Bay, Maine.

Student Qualifications

COSC student: some experience in coding, web-based applications
BIOL student: genetic experience desired but not required

Number of Student Researchers

2 students

Project Length

8-10 weeks

Applications open on 10/03/2023 and close on 02/28/2024

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If you have questions, please contact Karyn Belanger (