Gijs Burghoorn
Promovendus at Radboud University
Netherlands
Summary
🤩
Rockstar🎓
Top SchoolGijs Burghoorn is a Rust-focused hardware and security researcher with nine years of experience bridging systems programming and microarchitectural security. Currently a promovendus at Radboud University, he blends academic research on design-stage hardware vulnerabilities with hands-on development from prior roles including a Rust software engineer at Polars. At Polars he contributed deep internals work—refactoring IRs, optimizing memory use, and improving Parquet handling—demonstrating expertise in high-performance data processing. His background spans European research labs and engineering masters in cybersecurity and informatics, giving him both theoretical rigor and practical engineering chops. Notably, he combines low-level hardware security intuition with production-grade Rust contributions, a rare mix that helps turn subtle architectural issues into actionable fixes.
9 years of coding experience
3 years of employment as a software developer
Master of Science in Engineering Cybersecurity, Master of Science in Engineering Cybersecurity at National School of Computer Science and Applied Mathematics of GrenobleBachelor's degree Informatica, Bachelor's degree Informatica at Leiden University
Github Skills (13)
algorithm10
parquet10
data-structures10
data-handling10
algorithms10
datastructures-algorithms10
rust10
performance-optimization10
datatypes10
data-structure10
data-engineering9
parallel-processing8
data-analysis8
Programming languages (16)
Github contributions (5)
pola-rs/polars
Apr 2024 - Apr 2025
Dataframes powered by a multithreaded, vectorized query engine, written in Rust
Role in this project:
Back-end Developer & Data Engineer
Back-end Developer & Data EngineerContributions:143 reviews, 437 PRs, 64 pushes in 11 months
Contributions summary:Gijs's commits primarily focused on refactoring and implementing improvements within the Polars data processing library. Their work involved restructuring the internal representation (IR) for describing data, fixing bugs in data handling during scans and joins, optimizing memory utilization, and ensuring correct behavior for various data types. Additionally, they contributed to enhancing Parquet file handling with improvements to statistics loading and optimized encoding/decoding strategies for nested data structures. These changes demonstrate expertise in the internals of data manipulation and storage.
polarsdataframespythondataframerust
coastalwhite/cobs-rs
Mar 2021 - Jul 2022
A minimal heapless no-std Rust library to do Consistent Overhead Byte Stuffing
Contributions:14 commits, 2 PRs, 9 pushes in 1 year 4 months
rust-libraryno-stdstdcobs-algorithmconsistent
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