NEW: I recently finished my senior thesis in differential privacy methods in graph statistic computation. You can find it here.
I majored in computer science in my undergraduate years, so unsurprisingly I'm incredibly passionate about various topics in computation. Broadly, my main interests lie in programming languages, machine learning, and their intersection, e.g. machine learning compilers, PyTorch, etc. I'm also interested in topics in theoretical computer science and differential privacy.
I currently work at Facebook, where I work on building machine learning infrastructure for Facebook's personalization platform. I've interned at Facebook for two summers (2018 and 2019):
- During my first summer, I was on the Dynamic Ads team to help work on the foundations of the dynamic video ads template on Facebook.
- During my second summer, I was on the AI Infrastructure Feature Engineering team and developed a system to help machine learning teams at Facebook track the relationships and timelines of their features and models.
Check out my GitHub for some of my projects!
- Rusty Rubik: a Rubik's Cube representation and solver written in Rust. In development: a general-purpose puzzle solver.
- TorchLint: a device and matrix dimension linter for PyTorch programs written in Haskell.
I've also been a teaching assistant for several of Penn's classes: