Marc Haubenstock
Research Engineer at AIT Austrian Institute of Technology GmbH
Austria
Summary
👤
Senior🎓
Top SchoolMarc Haubenstock is a research engineer based in Austria with 14 years of software engineering experience focused on computer vision, sensor fusion and Rust development. Currently at the AIT Austrian Institute of Technology, he applies academic rigor from his TU Wien graduate work and a strong robotics background to real-world perception problems. He has industrial experience building probabilistic visual odometry and depth estimation systems, and contributed to nalgebra—adding complex-eigenvalue support—demonstrating comfort with low-level linear algebra and numerical methods in Rust. Comfortable across research and product contexts, he has a history of shipping robust C#/Unity features as well as Python tooling, reflecting a pragmatic approach to prototyping and production. Marc combines deep technical foundations from an Imperial College MEng with hands-on robotic experiments (ROS/Gazebo) and open-source contributions that bridge algorithmic clarity and engineering reliability.
14 years of coding experience
5 years of employment as a software developer
MEng, Computer Science, First Class Honours, MEng, Computer Science, First Class Honours at Imperial College LondonI.B Diploma/Austrian Matura Equivalency, 42/45, I.B Diploma/Austrian Matura Equivalency, 42/45 at Vienna International School
English, japanese b1
Github Skills (12)
vector10
vector-math10
rust10
matrix10
lapack10
linear-algebra10
algebra10
eigenvalue10
data-structure9
algorithm9
data-structures9
algorithms9
Programming languages (17)
Github contributions (5)
dimforge/nalgebra
May 2022 - Oct 2022
Linear algebra library for Rust.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:19 commits, 2 PRs, 18 comments in 5 months
Contributions summary:Marc focused on adding functionality to compute complex eigenvalues to the nalgebra library. The contributions involved modifying and extending the `eigen` module to incorporate complex number support, including handling complex eigenvectors and eigenvalues. The user's work included implementing a `get_complex_elements` method, refining existing methods and fixing formatting, all centered around linear algebra calculations and matrix decomposition.
eigenvalueslinear-algebra-librarylinear-algebrandarrayrust
geoeo/Dense_VO
Jun 2018 - May 2019
Implementation of Dense VO from Robust Odometry Estimation for RGB-D Cameras
Contributions:4 PRs, 197 pushes, 4 branches in 10 months
rgb-dodometryrgbestimationcameras
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