Bio
Dr William Moses is an assistant professor in the Computer Science and Electrical and Computer Engineering at University of Illinois Urbana-Champaign. He completed his PhD in Electrical Engineering and Computer Science (EECS) and at MIT, where he also received his M.Eng and BS in EECS and physics.
Research interests
Dr Moses' research involves creating compilers and program representations that enable non-experts to leverage the latest in high-performance computing and machine learning. He is known as the lead developer of Enzyme, an automatic differentiation tool for LLVM, the lead developer of Polygeist, a polyhedral compiler and C++ frontend for MLIR. He has also worked on the Tensor Comprehensions framework for synthesizing high-performance GPU kernels of ML code, the Tapir compiler for parallel program, and compilers that use machine learning to better optimize. He is a recipient of the US Air Force AI Accelerator Transition Award, the 2023 Julia Community Prize, a U.S. Department of Energy Computational Science Graduate Fellowship, and the Karl Taylor Compton Prize, MIT's highest student award.
His research work at the Turing focuses on Probabilistic Programming, in particular extending Turing.jl to facilitate collaborative, multi-dataset analyses through compositionality and modularity, enable Bayesian PPL-enabled analysis of huge data through embedding massive parallelisation and improve its usability through community consultation to inform improved application programming interface (API) design.