I completed my undergraduate degree at Brown University in Providence, Rhode Island.
One of my reasons for choosing Brown was its unique curriculum and educational philosophy. During my time at Brown I was able to obtain both bread and depth of study. My major (or "concentration" as they are called at Brown) was in Applied Mathematics, with a focus in physical sciences (physics and earth science). At the same time, I sampled courses across a range of disciplines including history, anthropology, economics, and philosophy.
Although Brown is a liberal arts institution, I attending Brown helped me get more involved in the sciences. Brown encourages students to take challenging courses outside their comfort zone by allowing them to take any course for a "satisfactory/no credit" grade; for me, this meant enrolling in my first mechanics course.
During my junior year, I spent the spring semester studying abroad in Scotland at the University of Edinburgh. Edinburgh was a great place to spend my semester abroad; the city is beautiful, walkable, and full of history. Edinburgh is often considered the birthplace of geology, so I was fortunate to take two courses in the university's School of Geosciences.
After a couple of years in the working world (read more about it here), I returned to academia.
I completed by graduate studies at Stanford University, earning my Ph.D. in Computational and Mathematical Engineering in June 2018. I received funding from a Stanford Graduate Fellowship in Science and Engineering, which provides three years of funding for graduate study. As a part of the PhD program requirements, I completed a Master of Science degree in Computational and Mathematical Engineering, which was conferred in June 2015.
My Ph.D. research on applications of data mining and machine learning techniques in earthquake seismology was supervised by Greg Beroza.