Ian Waudby-smith
Miller Postdoctoral Fellow at University of California, Berkeley
Berkeley, California, United States
Summary
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Senior🎓
Top SchoolIan Waudby-smith is a Miller Postdoctoral Fellow at UC Berkeley with 11 years of research and software engineering experience focused at the intersection of statistics, machine learning, and real-world reinforcement learning. He holds an MS and PhD in Statistics from Carnegie Mellon and has applied rigorous statistical methods in industry research internships at Google, Microsoft, and Adobe. His background spans health data science, robust and computational statistics, and applied ML, informed by early analytic roles in healthcare and financial software. Ian combines deep theoretical training (including work in analytic number theory and sieve methods as an undergrad) with hands-on development of research systems and experiments. Based in Berkeley, he is currently not seeking employment but continues to bridge academic inquiry and practical ML applications. A detail that stands out: his trajectory weaves pure math research into pragmatic data science problems, enabling novel approaches to noisy, real-world data.
11 years of coding experience
3 years of employment as a software developer
Doctor of Philosophy - PhD, Statistics, Doctor of Philosophy - PhD, Statistics at Carnegie Mellon UniversityHonours Bachelor of Mathematics (BMath), Statistics, Honours Bachelor of Mathematics (BMath), Statistics at University of Waterloo
Github Skills (63)
spss10
uniform10
decomposition10
emacs-lisp10
stata10
boundaries10
kebab-case10
emacs-lsp9
sampling9
melpa9
emacs9
vim9
sequential8
latex8
language-server8
Programming languages (11)
Github contributions (5)
WannabeSmith/confseq_wor
Oct 2020 - May 2021
Contributions:15 commits, 13 pushes, 1 branch in 6 months
WannabeSmith/dotfiles
Oct 2021 - Aug 2022
Contributions:4 PRs, 163 pushes, 4 branches in 9 months
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