About me

I’m a fourth year Computer Science Ph.D. student at MIT, advised by Martin Rinard.

Before coming here, I completed my M.S. in Computer Science at NYU, where I worked with Dennis Shasha on implementing AQuery, an optimizing compiler for order-related database queries. Before that, I worked for Morgan Stanley as part of the housing and mortgage research group. I graduated with a B.A. in Economics from University of Pennsylvania in 2011. I’m originally from San José, Costa Rica.

I am currently working at the intersection of software engineering and machine learning, and am interested in exploring applied machine learning research. Recently, I have spent most of my time working on applications of machine learning to healthcare, in particular using Electronic Health Records for early prediction of pancreatic cancer diagnoses. This is joint work with researchers at Beth Israel Deaconess Medical Center.

I have researched and published work on:

• optimizing database queries to perform dynamic imputation
• studying how developers use automatically generated bug patches
• using deep learning to improve code search using natural language
• applying active learning to infer and regenerate software
• using dynamic program analysis for automated machine learning

I’ve also worked on an assortment of other projects, such as using iOS data to customize image compression for users with color vision deficiencies, and performing large-scale color vision analysis across different countries.

Recently, I interned at Facebook (Summer 2018) with the BigCode team, and spent Fall 2018 working part-time as a researcher (“Research Collaborator”) with the same team. I am actively looking for summer internship opportunities for Summer 2020.