Minas Karamanis
Postdoctoral Fellow at University of California, Berkeley
Berkeley, California, United States
Summary
👤
Senior🎓
Top SchoolMinas Karamanis is a computational scientist and postdoctoral fellow at UC Berkeley and Lawrence Berkeley National Laboratory with nine years of experience building high-performance Bayesian inference tools for cosmology and astrophysics. He leads development of widely used open-source packages such as zeus and pocoMC and authors hankl, bringing practical, production-grade implementations of Monte Carlo and FFTLog methods to the community. His PhD from the University of Edinburgh, recognized with the Winton Award, produced novel gradient-free algorithms including Ensemble Slice Sampling that scale to highly correlated, black-box problems. Minas combines deep statistical modeling and scientific computing expertise with hands-on mentorship of students on projects from gravitational waves to exoplanet atmospheres, and is known for accelerating large-scale survey inference through preconditioned and sequential Monte Carlo techniques.
9 years of coding experience
Doctor of Philosophy - PhD, Astrophysics, Doctor of Philosophy - PhD, Astrophysics at The University of EdinburghMASt (Master of Advanced Study) in Applied Mathematics, Theoretical Physics, MASt (Master of Advanced Study) in Applied Mathematics, Theoretical Physics at University of CambridgeBachelor of Science with Honours (B.Sc. (Hons)), Physics, 9.16, Bachelor of Science with Honours (B.Sc. (Hons)), Physics, 9.16 at Aristotle University of Thessaloniki (AUTH)
English, Greek
Github Skills (58)
lightning10
cosmology10
python10
zeus10
machine-learning10
inference10
forge10
sampling10
mcmc10
bayesian-inference10
astronomy9
computation9
conda9
tensorflow9
bayesian9
Programming languages (5)
Github contributions (5)
minaskar/hankl
Jul 2020 - Jul 2020
Contributions:84 commits, 72 pushes in 20 days
minaskar/pocomc
Feb 2022 - Nov 2022
pocoMC: A Python implementation of Preconditioned Monte Carlo for accelerated Bayesian Computation
Contributions:136 commits, 60 PRs, 167 pushes in 9 months
pythonbayesian-inferencemonte-carlopymc3normalizing-flows
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