Northwestern University

Sep 2015 - Present

  • Pursuing PhD in Artificial Intellligence
  • GPA - 4.0 / 4.0
  • Advised by Ken Forbus
  • Awarded Cognitive Science Fellowship

Indiana University

Aug 2011 - May 2015

  • B.S. in Computer Science
  • Minor in Mathematics
  • GPA - 3.8 / 4.0
  • Advised by David Leake
  • Awarded the Dean's Advisory Council Senior Student Award

Work Experience

Jun - Sep 2018; May - Aug 2019

My primary focus while an intern at IBM was the development of neural-reasoning systems. In my first internship there, I wrote a superposition-based theorem prover that could be completely guided by deep-reinforcement learning techniques. Part of the work resulted in a patent application for discrete fixed-length vector-space encodings of structured data that were decodable. In the following summer, I developed method for encoding logical formulas with Graph LSTMs that resulted in significant performance improvements on premise-selection tasks. The LSTM encoding scheme also resulted in patent application.

May - Aug 2014

As an intern at Epic, I was tasked with writing a plagiarism detector that could automatically flag pairs of doctor notes with high degrees of similarity. The plagiarism detector was fairly simple, consisting of mostly trivial NLP similarity algorithms (e.g., Levenshtein distance).

May - Aug 2013

This was my first software engineering internship. I was on a team that was managing a data migration from Taleo to Peoplesoft. My objective was to develop a solution for streamlining grief report handling, thus helping to smooth the transition.