Martin Toeltsch
Managing Director at LeanFive IT GmbH
Austria
Summary
🤩
Rockstar🎓
Top SchoolMartin Toeltsch is a Managing Director with eight years of leadership at LeanFive IT GmbH and a deep academic background, holding a PhD in Telecommunications from TU Wien and an engineering degree in electrical and biomedical engineering. He blends technical research rigor with practical product delivery, steering a company while remaining hands-on in performance-critical software development. His open-source contributions include optimizing DeepSkyStacker with AVX intrinsics to accelerate median filtering and CFA image processing, demonstrating expertise in low-level optimization for image stacking workflows. That work reflects an ability to improve both algorithmic accuracy and throughput, a skill he applies to client projects and internal engineering practices. Based in Austria, he pairs systems-level engineering judgment with entrepreneurial experience, often tackling computational bottlenecks that others overlook. Colleagues know him for converting complex signal-processing concepts into efficient, production-ready implementations.
8 years of coding experience
Vienna University of TechnologyEngineer's degree, Electrical, Electronics and Communications Engineering, Biomedical Engineering, Engineer's degree, Electrical, Electronics and Communications Engineering, Biomedical Engineering at Technologisches Gewerbemuseum
English, German
Github Skills (6)
c-language10
cprogramming-language10
performance-optimization10
image-processing10
multithreading9
linear-algebra8
Programming languages (3)
Github contributions (5)
deepskystacker/DSS
Aug 2020 - Jan 2023
DeepSkyStacker
Role in this project:
Backend Developer
Backend DeveloperContributions:6 reviews, 259 commits, 13 PRs in 2 years 5 months
Contributions summary:Martin implemented AVX instructions to optimize image processing within the DeepSkyStacker project, focusing on improving the speed of median filtering and related operations. Their work involved modifying the `avx.cpp` and related header files, introducing conditional compilation using the `AVX_INTRINSICS` macro, and adding support for various data types and CFA image processing. The user's contributions also included refactoring, adding code for auto-adaptive weighted average processing, and addressing specific bugs to ensure the accuracy and efficiency of image stacking and filtering.
deep-learningpytorchcomputer-visionmachine-learning
mtoeltsch/DSS
Sep 2020 - Mar 2025
DeepSkyStacker
Contributions:520 pushes, 11 branches in 4 years 7 months
pytorchoptimizationssingerdeep-learningobjectmapper
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