Collaborate with the Straw Lab
The Straw Lab collaborates across neuroethology, animal behavior, ecology, computer vision, machine learning, robotics, and scientific instrumentation. We are especially interested in projects where a new measurement or modeling approach can make a previously inaccessible biological question testable.
Collaborations we are seeking
Drone-based tracking of insects in the field
We seek collaborations that use multicopter-mounted cameras and related sensor systems to measure insect flight and navigation in natural environments. Useful partnerships may contribute a study species, field site, ecological question, sensor or robotics expertise, or methods for analyzing three-dimensional trajectories.
Machine learning for insect tracking
We seek machine-learning collaborations that improve detection, pose estimation, identity preservation, calibration, uncertainty estimation, or trajectory reconstruction for insects recorded in laboratories or outdoors. The aim is robust scientific measurement rather than benchmark performance alone.
Machine learning for insect visual navigation
We are interested in models that connect visual input, memory, neural computation, and behavior during insect navigation. Potential projects can use measured trajectories, controlled virtual-reality experiments, neural data, or robotics-inspired models to generate biological predictions.
What the lab contributes
- Quantitative questions in honey bee and Drosophila navigation.
- Experience with synchronized multi-camera acquisition, real-time 2D and 3D tracking, moving cameras, and closed-loop experiments.
- Open-source systems including Braid, Strand Camera, and FLO.
- Experimental design, quantitative trajectory analysis, and a commitment to publishing reusable software and research outputs.
Review our research themes, software, publications, and funding and impact for examples.
Start a conversation
Email Andrew Straw with a concise description of the scientific question, the organism and experimental setting or available data, what each group could contribute, and any relevant funding route or timeline.