I am a postdoc at the University of Waterloo (since 2021), hosted by Gautam Kamath. My interests generally lie in CS Theory and Algorithms, though I mainly work on problems in the domain of Differential Privacy. I'm also interested in questions related to Statistics and Machine Learning, and my recent focus has been on the intersection of Privacy, Statistics, and Learning.
I got my PhD and master's in 2021 from Northeastern University, where I was fortunate to be advised by Jonathan Ullman. I was a Research Intern at IBM Research for Summer 2020, where I worked with Thomas Steinke. I visited University of Waterloo in Fall 2019, where I was supervised by Gautam Kamath. I was also a visiting graduate student at the Simons Institute for the Theory of Computing for their Spring 2019 program: Data Privacy: Foundations and Applications.
Prior to joining Northeastern University, I was an undergrad at the University of Southern California, graduating in 2016 with a bachelor's in Computer Science, and a minor in Mathematics. At USC, I had a wonderful opportunity to work with David Kempe on problems related to graphs.