Marco Rossi
AI Data Scientist
Harrisonburg, Virginia, United States
Summary
🤩
Rockstar🎓
Top SchoolMarco Rossi is an AI Data Scientist with a PhD in Electrical Engineering and eight years of experience building production-grade machine learning systems and experimentation platforms. He helped found Azure Personalizer at Microsoft and later worked in AI Frontiers on foundation-model tooling and learning agent platforms, blending applied research with product strategy and technical program management. His background spans online learning, contextual bandits, and human–AI decision systems, with contributions to the Vowpal Wabbit codebase and multiple patents in Microsoft’s AI portfolio. At Cortica he led efforts that dramatically improved image-to-text accuracy and speed, and he now focuses on AI-driven data pipelines to accelerate decision-making at Active Engagement. With 400+ academic citations and a track record of shipping real-world learning agents, he combines rigorous research instincts with pragmatic engineering and cross-functional leadership.
8 years of coding experience
11 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Electrical Engineering, Doctor of Philosophy (Ph.D.) Electrical Engineering at New Jersey Institute of TechnologyMaster of Science Telecomunications, Master of Science Telecomunications at Politecnico di Milano
French, English, Italian
Github Skills (12)
machine-learning10
bandit10
c-language10
cprogramming-language10
elearning10
python9
command-line-interface8
command-line8
cli8
searching8
reinforcement-learning7
active-learning7
Programming languages (8)
Github contributions (5)
VowpalWabbit/vowpal_wabbit
Jun 2018 - Nov 2022
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:2 reviews, 25 commits, 28 PRs in 4 years 5 months
Contributions summary:Marco primarily contributed to bug fixes and improvements within the Vowpal Wabbit codebase. Their work focused on correcting issues in CLI parsing, fixing bugs related to the handling of model loading, and addressing errors in the core learning algorithms. Furthermore, the user made enhancements and fixed bugs in the Python client library, focusing on improvements in documentation and example code. Their contributions touch on areas like Contextual Bandits, Online Learning, and general Machine Learning algorithm implementations within the C++ codebase.
hashingtechniquescpppythonactive-learning
marco-rossi29/mwt-ds
Oct 2017 - Oct 2019
Umbrella repository for projects related to the MWT Decision Service
Contributions:162 pushes, 17 branches in 2 years 1 month
umbrelladecision-serviceblockchaindecision
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