I am an Associate Research Scientist in the Department of Neuroscience at Yale University. focusing on computational neuroscience methods and neuroinformatics. Before my current position, I was a Postdoctoral Associate in Yale's Department of Computer Science researching the same. I have a Ph.D. in Mathematics from The Ohio State University (2011) and a M.S. in Computational Biology and Bioinformatics from Yale University (2015). I seek to combine the strengths of each of these fields to futher our understanding of the brain.
My interest in this interdisciplinary work dates to my time as an undergraduate student at the University of Maryland, Baltimore County where several of the math professors worked with questions in mathematical biology. My graduate institution is home to the Mathematical Biosciences Institute (MBI), which provided a steady exposure to interdisciplinary research. During grad school, I took a summer course on Computational Cell Biology at Cold Spring Harbor laboratory. This experience, combined with my advisor David Terman's focus on mathematical neuroscience, led to an interest in the role of cell biology, especially calcium dynamics, in neuron and network behavior.
As a postdoc, I continued to pursue this interest. I became a developer for the NEURON Simulator and designed and implemented its first official support for reaction-diffusion dynamics (McDougal et al 2013). I continue to improve this support by working on its performance, 1D/3D mosaic simulations, extracellular diffusion, and more. I program primarily in Python or C/C++. Simultaneously, I have been involved with studies using these dynamics to examine calcium wave propagation (Neymotin, McDougal, et al 2015) and possible roles for calcium dynamics in the maintenance of persistent activity (Neymotin et al 2016).
NEURON is developed out of the same lab that is responsible for ModelDB, a repository with source code over 1000 published computational neuroscience models. By interacting with my lab mates and developing my own models, I developed an appreciation for how complicated models can get and how hard it is to understand -- nevermind reproduce -- someone else's model. As such, I started to work to reduce the barrier: I implemented ModelDB's current search support, I added a ModelView tool (McDougal et al 2015) to ModelDB for visualizing model structure as an alternative to downloading and examining code, and I developed the ability to use 3D printing as a tool for neuron model visualization (McDougal and Shepherd 2015).
No one succeeds alone. As such, I value teaching and other outreach. In grad school, I taught Calculus and Differential Equations. More recently, I have taught about NEURON and ModelDB at NEURON courses. I have taught basic neuroscience to middle and high school students at department outreach events. In the summers, I have helped teach web development to mostly middle school students. I also do science fair judging.