Reza Zadeh - Founder CEO at Databricks

Reza Zadeh

Founder CEO at Databricks

Palo Alto, California, United States

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Summary

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Senior

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Top School

Reza Zadeh is a founder and CEO based in Palo Alto with 12 years of experience building applied machine learning and distributed analytics systems from research to production. He was on Databricks’ founding team contributing to Spark MLlib and has made notable open-source contributions to Apache Spark, including an SVD implementation for sparse matrices. As founder of Matroid he leads product and engineering efforts to deliver real-world computer vision and detection systems while teaching computational mathematics at Stanford. His background spans industry research roles at Twitter and Google internships that intersected with early translation and Transformer work, plus quantitative experience at Morgan Stanley. Comfortable at the intersection of academia and startups, he blends PhD-level theory with hands-on backend engineering to ship scalable ML infrastructure. He describes himself on GitHub as “Often fighting gravity,” a hint at his appetite for tackling hard engineering problems.

12 years of coding experience

5 years of employment as a software developer

Bachelors Mathematics Computer Science Software Engineering, Bachelors Mathematics Computer Science Software Engineering at University of Waterloo

Ph.D. Computational Mathematics, Ph.D. Computational Mathematics at Stanford University

Github Skills (11)

javas10

algorithms10

big-data10

spark10

svd10

linear-algebra10

java10

scala10

data-structure9

data-structures9

machine-learning8

Programming languages (3)

JavaScalaPython

Github contributions (5)

apache/spark

Jan 2015 - Sep 2015

Apache Spark - A unified analytics engine for large-scale data processing

Role in this project:

Back-end Developer

Contributions:3 PRs, 5 comments in 8 months

Contributions summary:Reza contributed significantly to the Apache Spark project, focusing on the implementation of a Singular Value Decomposition (SVD) algorithm for sparse matrices. Their work included the creation of core methods for the SVD, incorporating documentation, and refactoring code into a dedicated object. Further contributions involved test integration, implementing full and truncated rank matrix tests.

analyticspythondata-processingsqlapache

rezazadeh/spark

Mar 2014 - Oct 2014

Mirror of Apache Spark

Contributions:121 commits, 8 pushes, 3 branches in 6 months

spark-sqlspark-mlapachebig-dataspark

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