I’ve learned a lot from my first few weeks in graduate school. There are a lot of lessons to be found in any new place, and graduate school is not any different. From the mundane day-to-day changes to a whole different understanding of scientific communities, I think it’s safe to say that experiencing graduate school first hand has helped me see things differently already. I can’t wait to dive right into research in the coming weeks.
For my undergraduate thesis at Cornell, I laid out a theoretical foundation for an interactive visual tool that students could utilize to aid in learning the lambda calculus. Lambda calculus underscores some of the fundamental core of functional programming languages. Its simplicity and power often work as a useful model for semantic analysis. However, some of its abstractions often pose pedagogical challenges. Arguably some of the methods by which lambda calculus is instructed to newly-minted FPL students is wanting. This is where LambdaLab comes into play.
Shantanu Gore and I wrote a paper on the design and implementation of a learning-based text generator for our final project in Prof. Haym Hirsh’s undergraduate artificial intelligence class (CS 4701) at Cornell University. Our design aims to use methods from natural-language processing to generate realistic comments for the social media site Reddit.
Siva Somayyajula and I wrote a paper on the theoretical design of a refinement logics proof assistant for our final project in Prof. Bob Constable’s undergraduate applied logic class (CS 4860) at Cornell University. We also implemented such an assistant by following our design. We hope that our assistant makes it easier for students/researchers to work with proof assistants based on custom proof calculi via executables.
I’ve decided to start an academic blog! (Finally.) Stay tuned for all sorts of academic posts related to computer science (and otherwise) as I finish up my undergraduate studies and trudge through graduate school.