Mariano Soria
Adjunct Professor at Universidad Tecnológica Nacional - Facultad Regional Buenos Aires
Buenos Aires, Autonomous City of Buenos Aires, Argentina
Summary
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Senior🎓
Top SchoolMariano Soria is an adjunct professor and PhD-trained bioengineer specializing in biomedical signal processing and machine learning, with a focus on cardiovascular signals and automatic ECG heartbeat classification. With over a decade of academic and research experience spanning UTN Buenos Aires and the Aragon Institute of Engineering Research (I3A) in Spain, he combines rigorous algorithm design in MATLAB and Python with practical patient-adaptive approaches. His work bridges fundamental research and applied development, contributing to group projects within GIBIO and supervising advances in automated cardiac monitoring. Born and educated in Argentina, he brings international research experience and a penchant for translating signal-processing theory into robust clinical tools.
11 years of coding experience
M.Sc., Bioengineering, M.Sc., Bioengineering at Universidad de ZaragozaPhD, Signal Processing for Automatic Heartbeat Classification and Patient Adaptation in the ECG, PhD, Signal Processing for Automatic Heartbeat Classification and Patient Adaptation in the ECG at Universidad de Buenos Aires / UBAelectronic engineer, Ingeniería eléctrica y electrónica, electronic engineer, Ingeniería eléctrica y electrónica at Universidad Tecnológica NacionalTecnico, Electronica, Tecnico, Electronica at Colegio Pio IX
Stackoverflow
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Github Skills (30)
algorithms10
python-development10
qt10
python10
signal-processing10
spyder10
ide10
matlab10
language-server-protocol10
anaconda10
scipy9
scientific-computing9
ekg7
pdf6
pdf-viewer6
Programming languages (5)
Github contributions (5)
marianux/jupytest
Jun 2018 - Dec 2022
Contributions:83 commits, 178 pushes, 1 branch in 4 years 6 months
marianux/ecg-kit
Mar 2015 - Feb 2020
A Matlab toolbox for cardiovascular signal processing
Contributions:7 releases, 333 commits, 1 PR in 5 years
matlabsignal-processing
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