Xavier Coubez
Verified Expert in Engineering
Data Scientist and Developer
Aix-les-Bains, France
Toptal member since December 14, 2021
Xavier holds a PhD in particle physics and participates in one of the two main CERN collaboration projects. For five years now, he has been working as a postdoctoral researcher at Brown University (USA) and RWTH Aachen University (Germany), developing in-depth knowledge about deep learning. Xavier studied the performance of several generations of algorithms for 3D object identification and worked on medical imaging and genomics projects, eager to apply data analysis to medicine.
Portfolio
Experience
Availability
Preferred Environment
MacOS, Python, PyTorch, Django, Scikit-learn, Linux, Kedro
The most amazing...
...particle physics project I've worked on was to study the performance of several generations of deep learning algorithms for complex 3D object identification.
Work Experience
Biostatistician
ICANS
- Performed genome-wide association studies related to breast cancer. Created a Kedro workflow allowing for easy re-use of the whole analysis pipeline and possible re-cast.
- Reviewed from methodological and statistical perspectives over 30 clinical trial protocols at various stages of development, from idea to submission to regulatory bodies.
- Trained medical and PhD students and postdocs in data analysis and statistics. Built streamlit application, allowing clinical trial analyses (survival, hypothesis testing, etc.) to be run efficiently.
Postdoctoral Researcher
RWTH Aachen University
- Managed a group of physicists in charge of 3D object identification within the CMS collaboration for two years. Defined the group's priorities and ensured the continuous development of new algorithms and calibration techniques.
- Initiated a new calibration method to account for the difference between data taken at the Large Hadron Collider (LHC) and the simulation.
- Contributed to creating a new physics analysis targeting the study of Higgs boson coupling to a specific particle.
- Supervised bachelor, master, and PhD students while working on vertexing and object identification. Helped define scientific projects based on new developments in the field of deep learning.
Postdoctoral Researcher
Brown University
- Initiated an effort to semi-automate data quality monitoring and data certification using dimension reduction within a detector group of the CMS collaboration.
- Defined the structure of a new anomaly detection playground in the scope of a Django-based project to provide a platform for the comparison of various approaches to data certification automation.
- Contributed to physics analyses targeting the study of the Higgs boson properties.
- Supervised PhD students who were working on vertexing and object identification. Helped define scientific projects based on new developments in the field of deep learning.
Consultant
Freelance
- Developed an algorithm for early anomaly detection in the medical imaging process.
- Improved the potential patient management by allowing the imaging to stop early when an anomaly is detected.
- Compared expert knowledge and machine learning approaches to anomaly detection.
PhD
Université de Strasbourg
- Collaborated on a complex physics analysis, the study of the Higgs boson, adding a new analytical approach.
- Contributed to the development of a complex object identification algorithm.
- Led a group of physicists in charge of deploying object identification algorithms for data taking.
Experience
Medical Imaging Anomaly Detection
Anomaly Detection Playground
https://github.com/CMSTrackerDPG/MLplaygroundHeavy Flavour Tagging
https://moriond.in2p3.fr/2019/EW/slides/2_Monday/2_afternoon/7_Coubez.pdfEducation
Ph.D. Degree in Particle Physics
University of Strasbourg - Strasbourg, France
Master's Degree in Subatomic Physics and Astroparticles
University of Strasbourg - Strasbourg, France
Bachelor's Degree in Physics
University of Strasbourg - Strasbourg, France
Certifications
Generative Adversarial Network (GANs) Specialization
DeepLearning.AI via Coursera
AI for Medicine Specialization
DeepLearning.AI via Coursera
Deep Learning Specialization
DeepLearning.AI via Coursera
Skills
Libraries/APIs
Pandas, NumPy, Matplotlib, Beautiful Soup, PyTorch, Scikit-learn
Languages
Python, Python 3, C++, SQL
Paradigms
Anomaly Detection, Management
Platforms
Anaconda, MacOS, Linux, Docker, Kubernetes
Industry Expertise
Bioinformatics, Teaching
Frameworks
Selenium, Django, Kedro, Streamlit
Storage
MySQL
Other
Particle Physics, Data Analysis, Machine Learning, Data Science, Research, Deep Learning, English, APIs, Statistics, Algorithms, Technical Leadership, Statistical Data Analysis, Artificial Intelligence (AI), Science, Communication, Biostatistics, Mathematics, Genomics, Nuclear Physics, Physics, Medical Imaging, Generative Adversarial Networks (GANs), Dimensionality Reduction, Data Visualization, Explainable Artificial Intelligence (XAI), Outreach, Principal Component Analysis (PCA), Big Data, Scientific Computing, Scientific Data Analysis, Web Scraping, CI/CD Pipelines, Safety, Analysis, Genowe Wide Association Study
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