My research focuses on understanding biological principles of efficient sensing: how do animals allocate limited sensory resources to extract the most critical information from a high-dimensional and ever-changing environment? I employ a combination of experimental and computational techniques to investigate these questions, using models to understand biological systems and taking inspiration from biology to inform efficient sensing techniques.
Insects provide excellent model systems to investigate sparse and efficient sensing, as they exhibit impressive behavioral repertoires with exceptionally compact nervous systems. Flight systems in particular are strongly constrained by the need to be small, light, and fast. My work addresses how the hawkmoth (Manduca sexta) uses limited sensory information about wing deformation in order to achieve agile flight control. I record from sensory structures arrayed over the surface of the wings to determine which features of strain drive their responses. In parallel, I employ computational methods to assess how one might optimally array a set of these sensors to best provide feedback during flight. This work contributes to our understanding of efficient sensing in a biological system and advances general methods in sparse sensing.
- PhD, Neuroscience, University of Washington, 2019;
- BA, Biological Sciences, University of Chicago, 2011