I'm a recent graduate of the University of Michigan, where I studied Computer Science, Math and Linguistics!

I've done research in multimodal classifer optimality, semantic event complexity, neurosymbolic low-resource translation, geometric self-supervised learning theory, distributed LLM training, memory waves in general relativity, simulators for complex dynamics, and reverse mathematics systems.

Trust me, they all make sense together.

I've TA'd four graduate courses across SI, ECE and CSE (Applied ML, Data Science Math, LLM Theory + Pytorch, and Complexity Theory), and it might be my favorite way to work with people. Helping develop opinion is what I live for.

From grading and office hours, to helping make homeworks and lecture slides, all of it is so much fun.

I like making things for the oddly specific problems in my life, from my own jeans and a stenography keyboard to custom MIDI interfaces and a language for my mental grammar.

The common thread is my strong opinion and an investment in personalization.

Some of my favorite projects have been parallel CFD via hodge decomp, mean-field queueing dynamics, and HoTT for structured semantic equivalence.

I'm currently working on a projective harmonic lighting engine and on cross-kernel synthetic mathematics!