Krzysztof Kolasiński
ML R&D Team Leader at FORM
Cracow Metropolitan Area Poland
Summary
🤩
Rockstar🎓
Top SchoolKrzysztof Kolasiński is an ML R&D team leader based in Kraków with 11 years of experience bridging computational physics, GPU-powered computer graphics, and applied machine learning. He holds a PhD in condensed matter physics and has a track record of turning academic expertise in quantum transport and GPGPU into production-ready ML projects and image-processing tools. His open-source work includes writing GLSL fragment shaders and integrating real-time GPU filters for texture generation, while his ML experiments span TensorFlow pipelines, class resampling, and novel CNN variants. At FORM he leads research and productization efforts for ShelfWise.ai after multi-year engineering work at FORNAX.ai, demonstrating an ability to move models from research to deployed systems. Colleagues describe him as a problem-solver who blends low-level performance optimization with practical data-science-driven solutions.
11 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy (PhD) Condensed Matter and Materials Physics, Doctor of Philosophy (PhD) Condensed Matter and Materials Physics at AGH University of Krakow
English, Portuguese, Polish
Stackoverflow
1reputation
0reached
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Github Skills (15)
mask-rcnn10
keras10
faster-rcnn10
deep-learning10
tensorflow10
glsl10
shader10
opengl10
image-processing10
texture-mapping10
computer-graphics9
machine-learning9
regularization8
data-augmentation8
cifar1007
Programming languages (6)
Github contributions (5)
kmkolasinski/AwesomeBump
Dec 2014 - Mar 2020
AwesomeBump is a free program written using Qt library designed to generate normal, height, specular or ambient occlusion textures from a single image. Since the image processing is done in 99% on GPU the program runs very fast and all the parameters can be changed in real time. AB was made to be a new alternative to known gimp plugin called Insane Bump.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:18 releases, 197 commits, 27 PRs in 5 years 4 months
Contributions summary:Krzysztof primarily focused on the development of fragment shader code to generate normal, height, specular, and ambient occlusion textures from a single image. Their contributions involved writing GLSL code, implementing various filter modes and pixel-level manipulations, and integrating these filters into a larger OpenGL-based image processing application. The user was involved in adding multiple tools for image manipulation such as perspective and texture manipulations.
ambient-occlusionparametersambientgpusingle-image
kmkolasinski/deep-learning-notes
Nov 2017 - Jan 2020
Experiments with Deep Learning
Role in this project:ML Engineer
ML EngineerContributions:162 commits, 17 PRs, 136 pushes in 2 years 2 months
Contributions summary:Krzysztof contributed to experiments with Deep Learning, specifically focusing on implementing class oversampling/undersampling in a TF+datasets API. Further development included training a CNN with CapsulePooling2D. The user also added a SELU regularization and tested with a CNN on the CIFAR10 dataset, conducting experiments comparing different optimizers.
deep-learningpythonmachine-learningtensorflow
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