hello there!

I am a third-year PhD student in EECS at UC Berkeley, advised by Nilah Ioannidis. Previously, I studied EECS (SB '18, MEng '19) at MIT and worked as a software engineer at GRAIL.

research

My current academic interests are in applying machine learning and statistics to problems in computational genomics and human disease, the primary tool being deep learning models which predict functional activity from genomic sequence. See my research page for recent publications.

I previously worked with various groups at MIT CSAIL, including the Theory Group (on a biological algorithms problem), the ALFA group (studying learner behavior in MOOCs), and the Internet Policy Research Initative (studying privacy policies). I've also dabbled in climate science, telemedicine, bioengineering, and astrophysics.

education

Electrical Engineering & Computer Science at UC Berkeley.
PhD Student, 2022-?

Electrical Engineering & Computer Science at MIT.
SB 2018, MEng 2019.

Engineering at Queens' College, University of Cambridge.
MIT-Cambridge Exchange, 2016-2017.

Castilleja School. Class of 2014.

employment

From 2019-2022, I worked on data infrastructure as a software engineer at GRAIL. Previously, I interned at the New York Times and Sitka Technology Group.

teaching

Most recently, I was a Graduate Student Instructor for UC Berkeley's EECS 127/227A, Optimization Models in Engineering (Fall 2024). Before that, I was a lab and teaching assistant for a few MIT EECS classes, including Introduction to Machine Learning. I've also tutored, taught in a high school classroom, and staffed outreach programs.