Maxwell Hutchinson is an AI engineer with 13 years of experience at the intersection of software, methods development, and physical sciences, applying applied mathematics and physical reasoning to challenges in climate, sustainability, and equitable prosperity. He holds a PhD in Physics from the University of Chicago and has transitioned research-grade scientific software into productized materials informatics at companies like Citrine, Kiva, and Modular. Maxwell blends low-level performance work—contributing Fortran interfaces and numerical tests to high-performance libraries such as libxsmm—with higher-level ML and platform engineering to accelerate materials discovery and production AI. Comfortable in early-stage environments and moonshot projects, he pairs pragmatic engineering with domain depth to move ideas from prototype to impact. An often-overlooked strength is his track record of encoding domain knowledge and uncertainty into data models, making complex physical systems tractable for active learning and deployment.
13 years of coding experience
13 years of employment as a software developer
PhD, Physics, PhD, Physics at University of Chicago
Bachelor of Science (B.S.), Physics (Math, Computer Science), Bachelor of Science (B.S.), Physics (Math, Computer Science) at Carnegie Mellon University
Library for specialized dense and sparse matrix operations, and deep learning primitives.
Role in this project:
Back-end Developer
Contributions:74 commits, 8 PRs, 16 comments in 1 month
Contributions summary:Maxwell contributed to the Fortran interface of the library, focusing on handling beta values and hardcoding data types. The commits modified the Fortran interface file, scripts for interface generation, and the make files. Furthermore, they added a numerical test using the `CP2K` samples and added additional targets to the `make.sh` script.
Tools for converting from DFT codes into PIF objects
Contributions:124 commits, 94 PRs, 80 pushes in 2 years 9 months
convertingpifdft
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