Miguel Monteiro
Principal Research Scientist at Qureight
London, England, United Kingdom
Summary
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Rockstar🎓
Top SchoolMiguel Monteiro is a Principal Research Scientist based in London with eight years of experience building machine learning and computer vision systems for medical imaging, currently leading biomarker-extraction algorithm development at Qureight. He holds a PhD in Computer Science from Imperial College London and a strong engineering foundation from double degrees in Electrical and Computer Engineering and Wireless Systems, blending rigorous research with production-minded implementation. Miguel has led projects from CT lesion analysis for the EU CENTER-TBI consortium to industrial deep-learning segmentation pipelines and has hands-on experience tackling label noise and outlier detection from a Microsoft research internship. Known for translating academic advances into clinical-grade tools, he combines statistical rigor with practical system design and an eye for robust, deployable models. An underappreciated strength is his cross-domain background in time-series and network forecasting, which informs more resilient model engineering for healthcare applications.
9 years of coding experience
9 years of employment as a software developer
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Imperial College LondonDouble Degree Master's Wireless Systems, Double Degree Master's Wireless Systems at KTH Royal Institute of TechnologyDouble Degree Master's Electrical and Computer Engineering, Double Degree Master's Electrical and Computer Engineering at Instituto Superior Técnico
Portuguese, English, Spanish, Swedish
Github Skills (70)
python10
style-transfer10
medical-imaging10
cpp10
crf10
convolutional-neural-networks10
autoencoder10
dataclasses10
argparse10
omegaconf10
vnet10
environment-variables10
filter10
machine-learning10
segmentation10
Programming languages (5)
Github contributions (5)
biomedia-mira/blast-ct
Mar 2020 - Nov 2021
Brain Lesion Analysis and Segmentation Tool for Computed Tomography
Contributions:2 releases, 52 commits, 2 PRs in 1 year 8 months
segmentation
MiguelMonteiro/CRFasRNNLayer
Mar 2018 - Jan 2019
Conditional Random Fields as Recurrent Neural Networks (Tensorflow)
Contributions:28 commits, 8 pushes, 38 comments in 10 months
recurrent-neural-networkstensorflowcrfasrnn-tensorflowcrfasrnncrf
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