Dan Waxman
Cambridge, Massachusetts, United States
Summary
👤
Senior🎓
Top SchoolDan Waxman is a research-oriented postdoctoral scientist and MIT Research Affiliate with 11 years of experience specializing in Bayesian statistics, causal inference, and online/sequential learning for dynamical systems. Currently at Basis Research and collaborating with MIT's UQ group, he focuses on uncertainty quantification, ensembles, and experimental design informed by rigorous theory and interdisciplinary applications. He completed a PhD in electrical engineering at Stony Brook, where his dissertation developed practical sequential Bayesian methods and ensemble approaches for online inference. Comfortable both in deep theory and hands-on engineering, he has taught AI/ML literacy, built production-facing educational software, and contributed to large-scale Bayesian analyses for physics experiments. Colleagues value his knack for translating foundational math into deployable inference tools that address real-world, time-varying problems.
11 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy - PhD Electrical Engineering, Doctor of Philosophy - PhD Electrical Engineering at Stony Brook University
English, Persian
Stackoverflow
101reputation
4kreached
3answers
0questions
Github Skills (45)
probabilistic-programming10
compilation10
python10
animation10
cpu10
mcmc10
diffraction10
optimisation10
pyro10
probabilistic10
bayesian-inference10
autodiff9
sampling9
math9
gpu9
Programming languages (7)
Github contributions (5)
DanWaxman/danwaxman.github.io
Dec 2017 - Oct 2023
GitHub IO page with various personal projects.
Contributions:2 PRs, 100 pushes, 1 branch in 5 years 11 months
github-io-pagejsjavascriptpersonal-projects
spsStonyBrook/spsstonybrook.github.io
Aug 2020 - May 2023
Contributions:2 reviews, 36 PRs, 50 pushes in 2 years 9 months
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