I am a neuroscientist researching the mechanisms of cortical computation that give rise to sensory perception. Using statistical models and machine learning techniques, I characterize neuronal dynamics in primary sensory cortices and multi-sensory integration areas of the brain. I then model and simulate artificial neural networks of spiking units that replicate these neuronal dynamics. Probing spiking neural networks provides a circuit-level understanding of the brain's sensory processing.
I am currently a postdoctoral researcher at Carnegie Mellon University working with Brent Doiron and Matthew Smith. I recently defended my PhD in Neural Computation at Carnegie Mellon under the advisory of Brent Doiron and Valerie Ventura. My doctoral studies were funded in part by the US Department of Energy Computational Science Graduate Fellowship, which focused on high-performance computing. During this fellowship, I did a short research practicum on auditory coding at Lawrence Berkeley National Laboratory.
Prior to graduate school, I was a Whitaker International Fellow studying tactile coding in the peripheral nervous system with Richard Vickery at the University of New South Wales. I completed my Bachelors of Science in Bioengineering at the University of Pittsburgh where I did research on tactile and proprioceptive feedback for Brain-Machine Interfaces with the Rehab Neural Engineering Lab. Throughout this time, I was also employed by the Johns Hopkins University Applied Physic Laboratory, where I worked primarily on non-invasive neural technologies and ontologies and response strategies for cybersecurity attacks.