Alexandru Meterez is a Harvard CS PhD candidate specializing in deep learning theory and optimization, with nine years of engineering and research experience across academia and industry. He has held research internships at Max Planck and IBM, contributed to teaching at ETH Zürich and University POLITEHNICA of Bucharest, and applied ML in product settings at Adobe. His engineering work includes backend contributions to big-data MapReduce exercises used in ETH Zurich coursework, demonstrating practical fluency with Hadoop and scalable data-processing pipelines. Comfortable bridging theory and implementation, he blends rigorous academic research with hands-on system-building and pedagogy. Based in Cambridge, MA, he brings a pattern-seeking mindset to neural network optimization and large-scale computation.
9 years of coding experience
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Harvard University
Master's degree Data Science, Master's degree Data Science at ETH Zürich
POLITEHNICA București National University for Science and Technology
Exercises for the Big Data lecture at ETH Zurich (Fall 2021)
Role in this project:
Backend Developer
Contributions:7 commits, 6 pushes in 4 months
Contributions summary:Alexandru's commits focus on adding a new notebook related to MapReduce exercises. The user implements and refactors Java code for a MapReduce word count job, including considerations for using the Reducer as a Combiner. The commits demonstrate an understanding of the MapReduce programming model and the Hadoop ecosystem, involving tasks such as data loading, job execution, and result processing.
Contributions:5 pushes, 1 branch in 4 years 4 months
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