Francesco Ciompi
Associate Professor
Nijmegen, Gelderland, Netherlands
Summary
👤
Senior🎓
Top SchoolFrancesco Ciompi is an associate professor and research group leader specializing in artificial intelligence for precision medicine, with a decade of experience translating deep learning and computer vision into clinical-grade digital pathology and medical imaging tools. Based at Radboud University Medical Center in Nijmegen, he progressed from PhD work on intravascular ultrasound to senior researcher and faculty roles focused on lung cancer imaging, CT analysis, and computer-aided diagnosis. His work bridges rigorous academic research and applied clinical impact, leading projects that integrate discriminative and sequential models into pathology workflows. Trained in electronic engineering and AI/vision across Italian and Spanish universities, he blends systems-level engineering instincts with methodological depth in machine learning. Notably, his career path reflects a steady shift from foundational signal-processing and control systems toward leading translational AI in healthcare.
11 years of coding experience
10 years of employment as a software developer
Master of Science (MSc), Electronic Engineering, Master of Science (MSc), Electronic Engineering at Università di PisaMaster's degree, Artificial Intelligence and Computer Vision, Master's degree, Artificial Intelligence and Computer Vision at Universitat Autònoma de BarcelonaDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Universitat de Barcelona
Italian, English, Spanish, Catalan, Dutch, French
Github Skills (12)
javascript10
python8
gpu7
classification7
machine-learning7
deep-learning7
numpy5
neural-network5
tensor3
gpu-acceleration3
autograd2
command-line-interface1
Programming languages (3)
Github contributions (5)
francescociompi/stain-normalization-isbi-2017
Jan 2017 - May 2019
Stain normalization parameters used in the paper "F. Ciompi et al., The importance of stain normalization in colorectal tissue classification with convolutional networks, ISBI 2017"
Contributions:11 commits, 10 pushes, 1 branch in 2 years 4 months
classification
mitkovetta/nfbia15-deep-learning
Sep 2015 - Sep 2015
Contributions:1 commit, 1 push in 1 day
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