Duarte Folgado
Senior Scientist at NOVA School of Science and Technology
Lisbon, Lisbon, Portugal
Summary
🤩
Rockstar🎓
Top SchoolDuarte Folgado is a senior scientist with 12 years of experience applying signal processing, machine learning and deep learning to extract knowledge from time series, primarily in healthcare biosignal applications. Based at Fraunhofer AICOS in Lisbon, he leads research teams from prototyping to deployment while driving competitive R&D proposals at national and European levels. Duarte combines academic rigor—as a PhD candidate in Biomedical Engineering and a visiting researcher at MIT—with hands-on mentoring as an invited assistant professor and educator. He contributes to open-source tooling for time-series feature extraction, improving usability and documentation of the tsfel library to lower the barrier for practitioners. Outside the lab he pursues precision and discipline as an EASA certified flight instructor, a detail that informs his methodical approach to experiments and system design. His profile blends applied research impact, teaching, and practical engineering that accelerates translational health technology.
12 years of coding experience
9 years of employment as a software developer
PhD Student, Biomedical Engineering, PhD Student, Biomedical Engineering at Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa - FCT NOVAVisiting PhD Candidate, Artificial Intelligence, Visiting PhD Candidate, Artificial Intelligence at Massachusetts Institute of TechnologyColégio Militar
English, Portuguese
Github Skills (6)
time-series10
feature-engineering10
python10
documentation10
machine-learning9
data-science8
Programming languages (5)
Github contributions (5)
fraunhoferportugal/tsfel
Jan 2019 - Jun 2022
An intuitive library to extract features from time series.
Role in this project:
Data Scientist
Data ScientistContributions:28 releases, 9 reviews, 92 commits in 3 years 4 months
Contributions summary:Duarte primarily focused on improving the documentation, particularly the "Get Started" and "Contribution" sections, and updating the "FAQ." The user also fixed documentation issues and broken links, and addressed minor bugs related to specific features. In addition, there were updates made to the Colab example. The user's work focused on enhancing the user experience and maintaining the quality of the documentation.
time-series-analysisfeature-extractiondata-sciencemachine-learningintuitive
dmfolgado/tam
Dec 2017 - Jul 2022
Time Alignment Measurement for Time Series
Contributions:11 commits, 1 PR, 9 pushes in 4 years 7 months
dtwtime-series-analysisalignmentmeasurementmetrics
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