Paul Mineiro
Principal Researcher at Microsoft
Bellevue, Washington, United States
Summary
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Rockstar🎓
Top SchoolPaul Mineiro is a Principal Researcher at Microsoft with 18 years of experience building scalable machine learning systems across ads, search, social, cybersecurity, recommendations, and automated software engineering. He blends applied AI productization for cloud platforms with a strong research pedigree—authoring work in reinforcement learning, online learning, large language models, and confidence sequences. Paul has a proven track record shipping production ML at scale, from founding startups and building ad-serving optimization engines to contributing advanced neural components (dropout, input passthrough) to the influential Vowpal Wabbit project. His background spans both deep engineering (Erlang, low-latency systems) and quantitative leadership roles at companies like Yahoo, eHarmony, and ÜberMedia. Based in Bellevue, WA, he combines academic rigor (Caltech physics, cognitive science at UCSD) with pragmatic systems thinking and an appetite for integrating research into high-throughput products. An underrated strength is his ability to move between founding-stage scrappy implementation and large-company research-to-product delivery.
18 years of coding experience
9 years of employment as a software developer
University of California, San DiegoCalifornia Institute of Technology
Stackoverflow
190reputation
3kreached
7answers
3questions
Github Skills (14)
neural-network10
machine-learning10
c-language10
cprogramming-language10
elearning10
active-learning9
cpp9
reinforcement-learning7
bandit7
pytorch6
vowpal-wabbit6
sqlite6
sql6
hadoop6
Programming languages (7)
Github contributions (5)
VowpalWabbit/vowpal_wabbit
Nov 2012 - Nov 2020
Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.
Role in this project:
Back-end Developer & ML Engineer
Back-end Developer & ML EngineerContributions:21 reviews, 134 commits, 24 PRs in 8 years 1 month
Contributions summary:Paul contributed significantly to implementing and refining a 3-layer sigmoidal neural network within the Vowpal Wabbit project. Their work involved modifying the `nn.cc` and `parse_args.cc` files to incorporate features like dropout and input passthrough. These changes aimed to improve the model's performance and flexibility, enabling integration with other reduction techniques. The user appears to be focused on extending the machine learning capabilities of the library.
hashingtechniquescpppythonactive-learning
pmineiro/randembed
Jun 2015 - Nov 2015
Contributions:28 commits, 26 pushes, 1 branch in 4 months
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