I am a first-year PhD student in Computer Science at Cornell, working on compilers for accelerated computing. I’m interested broadly in realistic models of computation and the fundamental possibilities and limits of how computations can be mapped to the real world and implemented.
Before coming to Cornell, I spent three years at AMD as a computer architect in the Artificial Intelligence Group, working on AMD’s machine learning inference architecture, XDNA. I worked primarily on data movement programmability.
Before that, I completed my MS in Computer Science at UC Berkeley in 2022, where I was fortunate to be advised by John Wawrzynek, working on FPGA interconnect-CAD codesign and VLSI theory. Before that, I completed a BS in EECS in 2020, also at Berkeley.
If you’d like to talk, send me an email!