Xavier Tizon

(R&D, 2021-2022) Visualization and reporting of preclinical oncology experiments (R, shiny) (R&D, 2022) Classification of retinal images by deep learning – integration into a novel diagnostic device (deep learning, pytorch) (R&D, 2020-2021) Detection and classification on dental X-ray images using deep learning (deep learning, pytorch) (R&D, 2020) Statistical analysis of equivalence data on a novel biological test (R, statistics) (R&D, 2019) Modeling of PET imaging data for brain cancer radiotherapy treatment planning (R) (R&D, 2018) ML to predict side effects in patients eligible for refractive surgery (ophthalmology) (Scientific writing, 2021) Answer to a European grant proposal on explainable AI (Scientific writing, 2019-2020) Report writing for CIR (Crédit Impôt Recherche) – Computer vision, 3D, pharma (Teaching, 2018-) Mentor, “Data scientist” and “Machine learning engineer” tracks, Openclassrooms (Teaching, 2020) Project reviewer and mentor, “Deep Learning in medical imaging” (Manning publishing) (Teaching, 2018) Development of a machine learning and data science curriculum (banking sector)

Technical, scientific and strategic consulting in the context of a drug discovery startup Proof of concept of ML/DL approaches to help decision-making in drug discovery (predictive modeling, analysis of heterogenous and high-dimensional biological datasets, LLMs to mine scientific literature datasets…)

Participation in 3 client projects (principal data scientist within the client-dedicated team) Efficacy to effectiveness - Projection of efficacy data gathered in randomized clinical trials onto real-world databases to evaluate the real-life potential of novel therapeutics Chronic treatment schedule optimization - Modeling the risk of adverse events in patients follow-up during maintenance therapy Transportability of follow-up criteria - Surrogacy analysis of time-to-event variables in clinical trials R&D - Evaluation of an external package to model time-dependent biomarker data Evaluation of the internal training program for data scientists - propositions for improvements

Development of scientific partnerships to develop the use of machine learning and artificial intelligence in the context of clinical research in digestive oncology (medical imaging, clinical biostatistics, genomics…) Head of biometric services (biostatistics, data management and IT – 12 collaborators)

Research project: Dimensionality reduction in multispectral satellite imaging Teaching: electronics (B.Sc. introductory course), Image processing (M.Sc. level), Matlab and image processing (ESIREM engineering school, M.Sc. level)

Telephone Support (France and abroad) and functional validation of Laboratory Information Management Systems. Achievement: I was responsible for the pre-delivery stage of 2 new software products (validation, documentation, installation and training on beta-sites) involving new technologies like Intranet and relational databases. I travelled within France, and to Italy and Canada.