Marek Sokol
Doctoral Researcher at České vysoké učení technické v Praze
Prague, Prague, Czechia
Summary
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Senior🎓
Top SchoolMarek Sokol is a biomedical engineer and PhD candidate at CTU Prague specializing in AI-driven neuroscience and physiological monitoring, with eight years of experience bridging research and production-grade software. He contributes to space-focused biomedical projects—one selected by ESA for ISS experiments—and develops specialized hardware and software for monitoring human physiology and cognitive load in microgravity. His background spans research software engineering in virtual-reality mental health, autonomous robotic systems for military applications, and hands-on biomedical device work in a major military hospital. Marek is also an active open-source contributor, having implemented an advanced ECG R-peak detection method in the widely used NeuroKit2 toolbox. His profile uniquely combines extreme-environment field research (three months in Antarctica) with practical systems engineering for clinical and space contexts.
8 years of coding experience
4 years of employment as a software developer
Information Technology, Information Technology at Soukromá střední škola výpočetní technikyDoctoral degree, Biomedical engineering, Doctoral degree, Biomedical engineering at České vysoké učení technické v Praze
Čeština, English, German
Stackoverflow
1reputation
0reached
0answers
0questions
Github Skills (9)
algorithm10
data-structures10
algorithms10
python10
ekg10
data-structure10
signal-processing10
scipy9
heart-rate9
Programming languages (3)
Github contributions (5)
neuropsychology/NeuroKit
Nov 2022 - Nov 2022
NeuroKit2: The Python Toolbox for Neurophysiological Signal Processing
Role in this project:
Back-end Developer
Back-end DeveloperContributions:3 reviews, 8 commits, 1 PR in 2 days
Contributions summary:Marek focused on adding and refining an ECG R-peak detection method based on visibility graphs within the NeuroKit2 library. This involved implementing the "koka2022" method, integrating it into the main `ecg_peaks` function, and creating a corresponding cleaning method. The contributions also include necessary code updates, import adjustments, and documentation enhancements to incorporate the new functionality seamlessly. Furthermore, the user addressed some code formatting inconsistencies.
signalentropyheart-ratepythonneuroscience
sokolmarek/bachelors-thesis
Mar 2021 - Sep 2022
Contributions:271 commits, 23 pushes, 2 branches in 1 year 6 months
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