2/24/2026 SIAM News
CS professor William S. Moses has received the 2026 SIAM Activity Group on Supercomputing Early Career Prize for his development of general-purpose parallel compiler technologies, enabling domain experts to achieve automatic, high-performance optimization, which produces faster programs with a transformative impact on scientific computing.”
Written by SIAM News
Congratulations to the 2026 SIAM prize recipient, Siebel School of Computing and Data Science professor William S. Moses, who will be recognized at the 2026 SIAM Conference on Parallel Processing for Scientific Computing on March 3-6, 2026, in Berlin, Germany.
Dr. William S. Moses, University of Illinois Urbana-Champaign and Google, is the recipient of the 2026 SIAM Activity Group on Supercomputing Early Career Prize. Dr. Moses received the award "for his development of general-purpose parallel compiler technologies, enabling domain experts to achieve automatic, high-performance optimization, which produces faster programs with a transformative impact on scientific computing." He will deliver a prize lecture at SIAM PP26 titled "Making Waves in the Cloud: A Paradigm Shift for Scientific Computing through Compiler Technology."
The SIAM Activity Group on Supercomputing Early Career Prize is awarded every two years to one individual in their early career for outstanding research contributions in the field of algorithms research and development for parallel scientific and engineering computing in the three calendar years prior to the award year.
Moses is an assistant professor of computer science in the Siebel School of Computing and Data Science, the Department of Electrical and Computer Engineering and in the Coordinated Science Laboratory at the University of Illinois Urbana-Champaign. He received a Ph.D. in computer science, an M.Eng and a B.S. in electrical engineering and computer science, and a B.S. in physics from the Massachusetts Institute of Technology (MIT). He is also a researcher at Google DeepMind and Google Cloud.
Moses's research involves creating compilers and program representations that enable performance and use-case portability, allowing non-experts to leverage the latest in high-performance computing and machine learning. He is also the lead developer of Enzyme, a tool for LLVM and multi-level intermediate representation capable of differentiating code across a variety of languages; Polygeist, a polyhedral compiler and C++ frontend for MLIR; and Reactant, a tool that enables existing scientific code to run on distributed machine learning accelerators.
Dr. Moses has also worked on the Tensor Comprehensions framework for synthesizing high-performance GPU kernels of machine learning code, the Tapir compiler for parallel programs, and compilers that use machine learning to better optimize. He is a recipient of the 2024 ACM Special Interest Group on High Performance Computing Doctoral Dissertation Award, a U.S. Department of Energy Computational Science Graduate Fellowship, MIT's highest student award, the Karl Taylor Compton Prize. Learn more about Dr. Moses.
Q: Why are you excited to receive the award?
A: I am honored to receive SIAM Activity Group on Supercomputing Early Career Prize. Computing has quickly become the backbone of nearly all modern science. As such, the supercomputing community, as well as the broader SIAM community, counts within its ranks everyone from black hole scientists, AI engineers, infectious disease experts, chemists, and so many more. I am truly humbled that my colleagues have selected me for this recognition and I look forward to working together with them on many interesting problems to come!
Q: What does your work mean to the public?
A: Today, computing has become so fundamental to all fields of science that each physicist, chemist, and astronomer must earn a second Ph.D. in computing just to do their research. My work aims to enable everyone to effectively leverage computation without needing to become experts in computer science themselves. I work on compilers, which is a fancy term for code that writes other code. In particular, rather than requiring a scientist to understand how to expertly apply techniques like parallelism, security, and machine learning, my goal is to build compilers that can harness these developments automatically. Ultimately, this means that computer programs and all of the science built from them will be faster, safer, and smarter!
Q: Could you tell us about the research that won you the award?
A: The end of Moore's law and the increasing reliance on computation have led to an explosion of complex software packages and hardware architectures. While this has enabled an unprecedented level of flexibility in building applications, it also requires rewriting applications to efficiently support each combination of software paradigms (e.g., differentiable, encrypted) and hardware targets (e.g., CPU, GPU, TPU, FPGA, Distributed). This means that each new hardware generation or cluster often requires significant and costly application re-engineering.
Instead, we propose an alternative approach that automatically and efficiently translates programs written in one parallel programming model into another. This enables practitioners to continue to use and develop their existing codebases while concurrently being able to effectively leverage the latest chips. This work is especially relevant now as modern accelerators are being built for specific tasks like tensor computations or AI and not the specific workload you're intending to run.
To effectively perform such transformations, we needed to develop a compiler that could represent the parallelism and other device-specific attributes of modern hardware in a general form that does not assume how it is going to be executed. This idea is very powerful and enables not only translation to other devices, but also significant additional optimization—including for the original device!
Q: What does being a member of SIAM mean to you?
A: SIAM's membership represents an entire community of those leveraging computation and math to push the world forward. I have been fortunate to attend SIAM conferences on a variety of different topics, which include those both in my direct area of expertise as well as those outside my field. The reason SIAM is one of my favorite communities is how much it values interdisciplinary work and enables different communities to come together. The great ideas of the future will require collaboration between areas, just as we've seen with the great ideas of the past!
This article was originally published by the Society for Industrial and Applied Mathematics on February 24, 2026.
William S. Moses is an Illinois Grainger Engineering Assistant Professor of computer science and is affiliated with the Siebel School of Computing and Data Science, Electrical and Computer Engineering and the Coordinated Science Laboratory.