Peter Williams
Technical Lead at Center for Astrophysics | Harvard & Smithsonian
Cambridge, Massachusetts, United States
Summary
🤩
Rockstar🎓
Top SchoolPeter Williams is a Technical Lead at the IAU Minor Planet Center with two decades of experience applying astrophysics and software engineering to large-scale scientific infrastructure. He bridges research and production: a PhD-trained astronomer who has led radio-astronomy science programs and now directs technical operations for global minor-planet data at the Center for Astrophysics. Peter is a hands-on engineer and open-source contributor, with backend work on high-impact projects like the emcee MCMC toolkit and low-level XeTeX I/O adaptations for the Tectonic typesetting engine. He routinely builds and maintains HPC and desktop pipelines for terabyte-scale datasets, mentors distributed teams, and communicates complex results to both scientific and public audiences. Based in Cambridge, MA, he combines deep domain knowledge in radio interferometry and magnetospheric processes with pragmatic software craftsmanship that keeps critical scientific systems robust and interruptible-friendly.
20 years of coding experience
12 years of employment as a software developer
Bachelor of Arts (BA), Astronomy & astrophysics and Physics, High honors, magna cum laude, Bachelor of Arts (BA), Astronomy & astrophysics and Physics, High honors, magna cum laude at Harvard CollegeDoctor of Philosophy (PhD), Astronomy and Astrophysics, Doctor of Philosophy (PhD), Astronomy and Astrophysics at UC Berkeley
Github Skills (17)
c-language10
python10
python-multiprocessing10
c1110
mio10
c1710
mcmc10
iio10
nio10
multiprocessing10
multi-process10
cprogramming-language10
numpy9
pdf9
tex9
Programming languages (29)
Github contributions (5)
dfm/emcee
Mar 2014 - Jan 2017
The Python ensemble sampling toolkit for affine-invariant MCMC
Role in this project:
Back-end Developer
Back-end DeveloperContributions:6 commits, 1 PR, 4 comments in 2 years 10 months
Contributions summary:Peter primarily contributed to the core functionality and stability of the `emcee` library. They fixed API documentation errors, implemented a SIGINT-friendly pool wrapper for multiprocessing, and made the interruptible pool the default within the ensemble sampler. They also addressed an issue with the `PTSampler.run_mcmc()` function and corrected related documentation.
mcmc-samplerpythonprobabilistic-data-analysisensembleinvariant
conda-forge/xorg-xf86miscproto-feedstock
Jul 2018 - Sep 2024
A conda-smithy repository for xorg-xf86miscproto.
Contributions:3 PRs, 3 pushes, 1 comment in 6 years 3 months
condasmithyxorg
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