Andrei Barbu
Principal Applied Scientist at Amazon
Bellevue, Washington, United States
Summary
👤
Senior🎓
Top SchoolAndrei Barbu is a Principal Applied Scientist with 18 years of experience blending deep academic research and production-grade engineering, recently transitioning from a decade-plus tenure at MIT's CSAIL and CBMM to Amazon. He holds a PhD in AI, robotics and computer vision from Purdue and a BCS in Math/CS from Waterloo, and his work centers on grounding knowledge in the real world across robotics, vision, knowledge representation and neuroscience. Skilled across systems and languages—from kernels and low-level networked applications to C++, Scheme, Haskell and Prolog—he pairs theoretical depth in logic, statistics and compilers with hands-on systems experience. A long-time open-source contributor and co-maintainer of a Scheme→C toolchain, he has also driven practical enhancements to prominent projects like the IHaskell Jupyter kernel. Known for bridging symbolic and statistical approaches, he brings a rare combination of formal rigor and pragmatic implementation to applied AI problems.
18 years of coding experience
10 years of employment as a software developer
Postdoc AI/ML, Postdoc AI/ML at Massachusetts Institute of TechnologyPhD Artificial Intelligence Computer Vision Robotics Neuroscience, PhD Artificial Intelligence Computer Vision Robotics Neuroscience at Purdue UniversityBCS Mathematics/Computer Science, BCS Mathematics/Computer Science at University of Waterloo
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (6)
jupyter10
haskell10
ghc10
ipython9
jupyter-kernels9
build-automation7
Programming languages (14)
Github contributions (5)
IHaskell/IHaskell
Mar 2017 - Nov 2021
A Haskell kernel for the Jupyter project.
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:45 commits, 5 PRs, 17 comments in 4 years 8 months
Contributions summary:Andrei primarily worked on enhancing the IHaskell project, a Haskell kernel for Jupyter. They made changes across several files, including core evaluation, completion, and display functionalities. Their contributions demonstrate a focus on adapting the project to newer GHC versions and ipywidgets, as well as addressing code improvements and parser updates. These modifications highlight the user's involvement in maintaining and extending the project's core features.
kerneljupyter-notebookhaskelljupyterjupyter-kernels
abarbu/purdue-beamer
Jan 2010 - Mar 2013
Contributions:2 commits in 3 years 2 months
purduebeamerlatex-beamerlatexposters
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