Ant Transportation Networks

What do ant colonies and railroad systems have in common? Both serve to transport goods and individuals from place to place, and need to balance the often competing goals of doing so efficiently and at low cost, while also remaining robust to potential disruptions to the network. We are currently working to understand how simple organisms can work together in groups to create and maintain such transportation networks, using a multidisciplinary combination of field and laboratory experiments with turtle ants, along with mathematical and computational models.

Project 1 (Engineering/CS/Biology): One important part of this work is the ability to efficiently describe real transportation networks created by turtle ants in their natural habitat: mangrove trees in the Florida Keys. Our first goal is to map out the spatial location of all ant nests in a tree, and describe the potential pathways between them. While this can be done by hand, we would like to develop a method for documenting the 3D structure of a tree using terrestrial laser scanning and/or photogrammetry, based on existing methodology known as quantitative structural modeling. Our second goal is to quantify the movement of ants along specific paths within a tree. We have already developed a physical framework and software pipeline to automatically track ant movement from videos taken in the lab. We would like to modify and test both the hardware and software to work effectively in a more challenging outdoor environment.

Project 2 (Biology/Engineering): A second key part of this work is testing the behavior of turtle ants in laboratory experiments. How do individual ants explore branching tree-like structures as they search for food and nesting resources? Do ants communicate about their discoveries, either indirectly via pheromones or directly by following one another? How do groups of ants choose new nests and create pathways for transporting resources between them? We would like to design and build a modular set of tree-like structures for ants to explore in the lab, and design and conduct a set of individual and group level behavioral experiments to answer these questions.

Project 3 (Math/CS/Biology): A third part of this work is modeling the behavior of groups of turtle ants moving along such tree-like structures. This behavior can be modeled computationally with agent-based models implemented in NetLogo or Python, and mathematically using the theory of random walks on graphs, systems of differential equations, or network flow models. By comparing the model outputs with the empirical data, we can begin to understand how individual rules of movement, coupled via communication, can generate the group behaviors we observe in real ant colonies.

Essay Prompt: What interests you about these projects and what do you hope to gain from the research experience? What makes you a good fit for one or more of these projects?

To complete your application for summer research in Biology, please contact me to discuss the project and submit this google form by Feb 28. If you have any questions or want to learn more, I encourage you to contact me before submitting your application.

Name of research group, project, or lab
The HMC Bee Lab
Why join this research group or lab?

You will be part of a team of students working on a set of related interdisciplinary projects, using mathematics, computation and engineering to solve problems of biological interest. The variety of techniques and approaches will give you an opportunity to explore your interests and develop new skills. These summer research projects are part of a larger NSF-funded collaborative research project, so you will interact with and present to a larger research group including graduate students and postdoctoral researchers at George Washington University and the University of York. There may be opportunities to continue the work in a senior thesis, present at a regional or national conference, and/or co-author future publications.

Representative publication
Logistics Information:
Project categories
Computer Science
Computational Biology
Computer Vision
Machine Learning
Mathematical Biology
Numerical Modeling
Student ranks applicable
Student qualifications

Students must have an interest in the complexity of the natural world and in the application of quantitative tools and models to understand it. First and second-year students still exploring their interests are encouraged to apply, as well as more advanced students in Math, CS, Engineering and Biology looking to apply their skills to practical problems across disciplinary lines.

Here is a list of skills/interests that could be useful, or which you might develop along the way. Don't let this long list intimidate you! They're not requirements, but if you already have experience or interest in any of them, be sure to mention it in your essay.

  • Programming in MATLAB and/or Python (Projects 1 and 3)
  • Linux/UNIX command line and shell scripting, high performance computing (Project 1)
  • Computer vision and image processing, e.g. using MATLAB or OpenCV (Project 1)
  • Data science and visualization, particularly with R (all projects)
  • Graph theory, geometry, networks (Projects 1 and 3)
  • Stochastic processes, dynamical systems, mathematical modeling (Project 3)
  • Raspberry Pi microprocessers (Projects 1 and 2)
  • Machine shop certification or other shop experience (Projects 1 and 2)
  • Computer-aided design, e.g. AutoCAD (Projects 1 and 2)
  • Animal behavior and/or insects, especially ants (all projects, especially Project 2)
  • Experimental design and statistical analysis (Project 2)
Time commitment
Summer - Full Time
Paid Research
Number of openings
Techniques learned

Depending on interests and experience: students will

  • create and/or contribute to a software pipeline combining MATLAB and Python
  • design and conduct laboratory experiments with insects
  • create mathematical and/or computational models of complex systems
  • extract, analyze and visualize data from any of the above

All students will learn to read and discuss scientific literature, and to communicate across disciplinary boundaries and with the public about their work.

Contact Information:
Mentor name
Matina Donaldson-Matasci
Mentor email
Mentor position
Associate Professor of Biology
Name of project director or principal investigator
Matina Donaldson-Matasci
Email address of project director or principal investigator
4 sp. | 32 appl.
Hours per week
Summer - Full Time
Project categories
Computer Science (+8)
BiologyComputer ScienceEngineeringMathematicsComputational BiologyComputer VisionMachine LearningMathematical BiologyNumerical Modeling