About me

I’m a senior researcher on the PROSE team at Microsoft, where we develop state-of-the-art program synthesis technologies to make software development more accessible, productive, and fun.

Before joining Microsoft, I received my PhD from MIT, under the supervision of Martin Rinard.

You can find a copy of my thesis here. The results of my thesis research also originally appeared in:

• using dynamic program analysis for automated machine learning (AutoML)
• generating AutoML search spaces using API docs and code corpora
• mining nearby transformations of machine learning pipelines to improve their performance

Closely relatedly, I have recently worked on:

• evaluating the empirical impact of downsampling as a way to scale genetic-programming-based AutoML to large datasets
• mining data wrangling functions from collections of Python programs written to work with the same dataset

I have also 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
• developing a risk prediction model for pancreatic cancer using electronic health records

Before my PhD, I obtained an M.S. in Computer Science (NYU) and a B.A. in Economics (University of Pennsylvania). I have had the opportunity of working (both as an intern and full-time employee) across technology and finance companies, in a variety of roles. I’m originally from San José, Costa Rica.