I recently graduated with a PhD from the Program in Plasma Physics within the Department of Astrophysical Sciences at Princeton University. In 2017, I graduated from the University of Pennsylvania (Summa Cum Laude) with a B.A. in Physics and a minor in Computer Science, where I was one of only two students in my graduating class to be selected as a junior for both Phi Beta Kappa and the Dean's Scholar Award. I was also awarded the Frazier Award, given to the graduating student-athlete (male or female) with the highest GPA who competed on one of the following teams: basketball, crew, track, soccer, baseball or football. As an undergraduate, I worked on computational plasma physics with Professor James Drake at the University of Maryland and with Professor Samuel Cohen at Princeton University. I also served as an undergraduate TA for PHYS101 and spent hundreds of hours tutoring a number of 100-level, 200-level, and 300-level physics courses.

My research interests span the fields of scientific computing, machine learning, plasma physics, nuclear fusion energy, and nuclear policy. At Princeton, I worked mainly on machine learning and automatic differentiation as applied to problems in nuclear fusion energy and plasma physics. I took 17 courses here, including a bunch of plasma physics classes, COS324 (Introduction to Machine Learning) and COS597 (Topics in Automatic Differentiation) with Ryan Adams, COS485 (Neural Networks) with Sebastian Seung, SML505 (Modern Statistics) with Peter Melchior, SPI548 (Weapons of Mass Destruction) with Christopher Chyba, as well as FRE101 and FRE102. In Spring 2020 I volunteered to TA for AST309 (The Science of Fission and Fusion Energy), taught by Professor Robert Goldston. 

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