Princeton Undergraduate Thesis: Sampling Strategies for Bayesian Optimization

For my undergraduate thesis at Princeton, I worked on generalizing Bayesian optimization (an algorithm used to optimize noisy, black-box functions) to scenarios where the amount of noise added to observations of the objective function varies across the domain. This project was advised by Prof. Jonathan Pillow, and I continued working on it in his lab for the summer after graduating.

You can read my thesis here.

REU Project: Sentence Simplification for Question Generation

During an REU fellowship at the University of Colorado Colorado Springs (UCCS) in 2014, I worked with Prof. Jugal Kalita and Feras Al Tarouti on developing a method for automatically generating simple comprehension questions from natural language sentences. This work was presented at the International Conference on Computing and Communication Systems at North Eastern Hill University, Shillong, Meghalaya, India, in April 2015.

You can read the conference paper here.