Maryam Majzoubi is a software engineer and PhD candidate at NYU with nine years of experience building scalable ML systems and algorithms for large-scale classification, contextual bandits, and continual learning. She blends academic rigor with production engineering—contributing to Vowpal Wabbit and implementing TensorFlow APIs for embedding compression during a Google internship. Now at Google as a software engineer, she focuses on turning online learning research into efficient, deployable solutions. Her background spans research collaborations at Microsoft and graduate work at Penn State, reflecting strengths in both theory and applied systems. Notably, she brings a rare combination of hands-on open-source contributions and deep expertise in online modular approaches for high-dimensional, real-time decision problems.
9 years of coding experience
6 years of employment as a software developer
Master of Science - MS, Electrical Engineering, Master of Science - MS, Electrical Engineering at Penn State University
Doctor of Philosophy - PhD, Electrical and Computer Engineering, Doctor of Philosophy - PhD, Electrical and Computer Engineering at New York University
Bachelor of Science (B.S.), Electrical Engineering, Bachelor of Science (B.S.), Electrical Engineering at Sharif University of Technology
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.
Contributions:47 PRs, 133 pushes, 2 branches in 1 year 2 months
Contributions:3 pushes, 1 branch in 1 year 9 months
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