Andreas Munk
Founder CEO at Evara
Vancouver, British Columbia, Canada
Summary
👤
Senior🎓
Top SchoolAndreas M. is a founder-led software engineer and researcher based in Vancouver, blending 8 years of hands-on development with deep Bayesian and probabilistic programming thinking. As founder and CEO of Evara, he is building tools to democratize probabilistic programming and the Bayesian mindset across teams and domains. He is currently pursuing a PhD in Computer Science at the University of British Columbia, where his research intersects machine learning, statistics, and computation. His background spans mathematical modeling from DTU and Earth- and Space-physics engineering, giving him a broad systems perspective from theory to applied tech. He has experience as a teaching assistant across multiple universities and was part of the CDL-Vancouver Compute cohort, reinforcing his commitment to mentoring and early-stage innovation. Based in Canada, he fuses academic rigor with entrepreneurial drive to turn probabilistic thinking into practical, scalable software solutions.
9 years of coding experience
1 year of employment as a software developer
California Institute of TechnologyDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at The University of British ColumbiaBachelor of Science (BSc), Earth and Space Physics and Engineering, Bachelor of Science (BSc), Earth and Space Physics and Engineering at Danmarks Tekniske UniversitetTechnical University of Denmark
English, Danish, German
Github Skills (55)
emacs-lisp10
emacs10
testing9
compilation9
emacs-lsp9
melpa9
probabilistic9
vim9
distro8
angular8
react8
probabilistic-models8
vue8
webpack8
javascript8
Programming languages (4)
Github contributions (5)
ammunk/Bayesian-Non-Parametric-NMF
Feb 2018 - Mar 2023
Contributions:10 pushes, 1 branch in 5 years 1 month
ammunk/pyprob
Mar 2019 - Feb 2023
A PyTorch-based library for probabilistic programming and inference compilation
Contributions:295 commits, 1 PR, 298 pushes in 3 years 11 months
pytorchcompilationdeep-learninginferencemachine-learning
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