Federica Eduati
Associate Professor
Eindhoven, North Brabant, Netherlands
Summary
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Senior🎓
Top SchoolFederica Eduati is an Associate Professor and computational systems biologist with 14 years of experience combining mechanistic mathematical modeling and machine learning to decode why cancer patients respond differently to therapy. She builds dynamic signaling-pathway models and leverages biomarker-driven approaches to suggest personalized treatments, translating models into actionable insights through a microfluidics platform that screens live patient biopsy cells within 48 hours and at low cost. Her interdisciplinary path spans wet-lab experiment design and hands-on microfluidics development alongside close collaboration with clinicians and biologists, reflecting a rare blend of computational rigor and experimental practice. Federica led community challenges such as co-organizing the 2013 DREAM Toxicogenetics Challenge, demonstrating commitment to open, collaborative problem solving at scale. Based in Eindhoven, she progressed from PhD work on multiscale insulin signaling to Marie Curie–funded postdoctoral projects at EMBL and academic leadership roles at RWTH Aachen and TU/e. Colleagues value her for tackling translational problems that bridge models, experiments, and clinical relevance.
14 years of coding experience
10 years of employment as a software developer
Master of Science (MSc), Bioengineering, 110/110 summa cum laude, Master of Science (MSc), Bioengineering, 110/110 summa cum laude at Università degli Studi di PadovaErasmus student, Erasmus student at Universitat Pompeu Fabra
English, Spanish, Italian
Github Skills (17)
biomedical9
medical8
biology8
r-package8
boolean-logic8
imaging7
braille7
medical-imaging7
logic6
machine-learning6
python6
boolean6
deep-learning5
collaboration4
data-analysis4
Programming languages (1)
Github contributions (5)
saezlab/CNORode2017
Feb 2017 - Feb 2020
Contributions:1 release, 33 commits, 34 pushes in 2 years 11 months
saezlab/BraDiPluS
Nov 2014 - May 2018
BraDiPluS (Braille Display Plugs Data Analysis) is an R package to process and analyse data produced using the microfluidic platform for functional drug screening of patient biopsies developed in collaboration with Merten group (EMBL).
Contributions:2 releases, 77 commits, 4 PRs in 3 years 6 months
r-packagedata-analysisscreeningbraillepatient
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