Phillip Cloud
Principal Software Engineer at NVIDIA
United States
Summary
🤩
Rockstar🎓
Top SchoolPhillip Cloud is a Principal Software Engineer with 13 years of experience building high-performance analytics, data-format, and systems software, currently at NVIDIA after leading platform work at Voltron Data. He combines systems programming (including Rust), computer vision and digital video experience with deep data-engineering expertise, contributing to flagship open-source projects such as Apache Arrow, Parquet, DuckDB and Substrait. Phillip’s contributions span protocol/refactor work, SQL dialect transpilation, decimal/fixed-width type support and build/CI improvements that enhance interoperability and developer workflows. He brings research-honed rigor from a psychology/neuroscience background—having analyzed neurophysiological datasets—which informs his methodical approach to performance and correctness. Known for a dry sense of humor and a fondness for puns, he blends curiosity with pragmatic engineering to tackle complex cross-language and system-level problems.
14 years of coding experience
13 years of employment as a software developer
Bachelor of Science (B.S.), Psychology, Bachelor of Science (B.S.), Psychology at City University of New York City College
Stackoverflow
25,219reputation
6.6mreached
221answers
5questions
pandas
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dataframe
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foreach
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pyspark
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Github Skills (129)
dependency-management10
dataanalysis10
parserator10
decimals10
parser10
documentations10
python10
nix10
testing10
postgres10
databases10
ipython10
cmake10
apache-arrow10
postgrest10
Programming languages (17)
Github contributions (5)
ibis-project/ibis
Nov 2015 - Jan 2023
the portable Python dataframe library
Role in this project:
Back-end Developer
Back-end DeveloperContributions:5630 reviews, 1970 commits, 6774 PRs in 7 years 4 months
Contributions summary:Phillip's commits primarily involve testing and implementing features within the Ibis project, a portable Python dataframe library. Their work includes debugging and skipping broken tests related to various database backends like Polars and PySpark. They also contribute to the core functionality by adding and refactoring features for array handling and database interactions, as seen in the modifications to the array functions and timestamp range implementations. Furthermore, the user is responsible for testing the performance of Ibis in various environments and for ensuring integration with several databases by creating specific configurations and test fixtures.
polarspythondaskdataframesdata-science
blaze/blaze
Jul 2014 - Dec 2015
NumPy and Pandas interface to Big Data
Role in this project:Back-end Developer & Data Engineer
Back-end Developer & Data EngineerContributions:6 releases, 1896 commits, 321 PRs in 1 year 5 months
Contributions summary:Phillip primarily focused on enhancing the back-end capabilities of the Blaze library, particularly in relation to time series and SQL database operations. Their commits introduced functionality to handle new data types like timestamps, implemented tests for comprehensive functionality, including time series and foreign keys, and they optimized database interactions for performance gains. Additionally, the user contributed improvements for the use of arithmetic operations, data type conversions, and the integration of SQL features.
data-analysispythondata-sciencenumpymachine-learning
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