Francisco聽Algarra
Postdoctoral Research Assistant at Queen Mary University of London
London, England, United Kingdom
Summary
馃懁
Senior馃帗
Top SchoolFrancisco Algarra is a computational scientist and postdoctoral researcher at Queen Mary University of London with 12 years of experience applying machine learning to real-world problems from music analysis to (epi)genomics. He designs robust experimental methodologies to ensure rigor and interpretability in applied ML, blending signal processing, statistics, and domain knowledge. Trained as an electrical engineer with a PhD and a master's in Sound and Music Computing, he moves comfortably between academic research and hands-on data analysis collaborations in clinical settings. Known as a "jack of all trades," he pairs broad technical curiosity with a focus on reproducible, well-grounded science, often translating complex models into experimentally verifiable insights.
12 years of coding experience
1 year of employment as a software developer
Master's degree, Sound and Music Computing, Master's degree, Sound and Music Computing at Universitat Pompeu FabraUPC Universitat Polit猫cnica de CatalunyaDoctor of Philosophy - PhD, Electrical, Electronic and Communications Engineering Technology/Technician, Doctor of Philosophy - PhD, Electrical, Electronic and Communications Engineering Technology/Technician at Queen Mary University of LondonLicenciado, Administraci贸n y Direcci贸n de Empresas, Licenciado, Administraci贸n y Direcci贸n de Empresas at Universitat de Barcelona
English, French, Catalan, Spanish
Stackoverflow
178reputation
30kreached
5answers
4questions
Github Skills (66)
guppy10
structural-variation9
estimate9
bioinformatics9
marginal-effects8
fastq-files8
next-generation-sequencing8
genomics8
variable-selection8
sequencing8
pairwise8
predict8
htslib7
linear-models7
r-package7
Programming languages (8)
Github contributions (5)
franrodalg/electronic-music-stylometry
May 2014 - Jul 2014
Contributions:41 commits in 2 months
franrodalg/pfc
Mar 2015 - Jul 2015
Contributions:51 commits in 4 months
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