Personal Statement
It was toward the end of high school when I discovered the excitement of seeking to understand the brain. Specifically, the spark for me came with the realization that the intense emotions evoked by listening to music — joy, sorrow, angst — originate from tiny fluctuations of air pressure entering the ear. How can the brain create such rich, subjective experiences from a one-dimensional signal?
In my first year of undergrad at Brown University, I filled my schedule with courses related to that question. I was hooked and went on to concentrate in neuroscience. I completed my Ph.D. at New York University working with Dan Sanes. My dissertation investigated temporal coding schemes in the olfactory bulb and in the auditory cortex, using single-cell electrophysiological data combined with computational analyses. During grad school, I discovered that communicating about science provided a different flavor of challenge and gratification complementary to that of performing research. After grad school, I set out to build skills in teaching and mentorship, first as an adjunct instructor at Santa Clara University and then as a teaching assistant professor at West Virginia University, and these experiences solidified my love of working with undergraduate students.
My role at Harvard combines my favorite aspects of these prior positions. As a concentration advisor, I work with the Class of 2026 neuroscience concentrators on shaping their academic and professional paths. As an instructor, I lead an introductory course on computational neuroscience. Computational tools are becoming a larger and larger part of contemporary neuroscience research, but they still have an intimidating reputation. A major goal of the course is to make these tools accessible both at conceptual and practical levels to students with all sorts of backgrounds and identities. Lastly, I keep a foot in research; my most recent publication investigates neural coding of temporally-dynamic sounds including human speech, and I am currently pursuing data analysis and modeling projects with collaborators.
Work-life balance is important to me. You’ll often find me outside — hiking, biking, gardening, or in a park with my dog. Ask me about podcasts, home renovation, and balancing time as a student-athlete.