Administrative tasks for booking platforms like Booking.com, Airbnb, and VRBOCustomer Service and Customer experience in French, English and SpanishData Structuration for PMS Integration

Recruited and trained volunteers for reception, website, and social media rolesEstablished local partnerships in the tourist industryDeveloped hiking trails and contributed to OpenStreetMap for hostel activities

Increasing diabetes cases, particularly type 2 diabetes mellitus (T2DM), have raised global health concerns. Due to the high prevalence of comorbidities and secondary diseases, such as cardiovascular disease (CVD), T2DM patients face many healthcare challenges. Access and the need for continuous medical care make T2DM care challenging. By providing continuous monitoring and personalized care, smartphones and artificial intelligence can reduce the burden of T2DM care for patients and healthcare professionals. My internship focused on the early development of a CVD risk assessment AI model for T2DM patients.- Thorough scientific literature research of cerebrovascular risk factors of diabetic patients- Search, evaluation and selection open-access datasets suited for the research questions- Data-wrangling, preliminary analysis, feature selection and matching using e.g. Scikit- learn, Pandas Python packages- Exploring unsupervised clustering and manifold learning methods such as KNN, UMAP, T-SNE- Training, evaluating Machine Learning models (e.g. Random Forest, Neural Networks) via multiple metrics of classification/prediction performance- Analysis of learnt feature representations, model transfer and interpretation on other populations of patients- Further exploring model behavior through explainable AI methods such as variable significance ranking using techniques such as SHAP analysis- Exploring various Data and Feature visualization techniques for better interpretation and discussion of results with e.g. Plotly

A collaborative project between IRIT (Research Institute of Informatics of Toulouse) and Restore (Geroscience and rejuvenation research center) Statistical analysis of immunostained adipose tissue images from confocal microscopy. Development of machine learning models to predict immunostaining reactions based on nuclei analysis (morphology, size, etc). (scikit learn, pandas, NumPy, OpenCV,XGBOOST)

Notetaker for person with disabilities in Biochemistry, Molecular Biology and Microbiology classes

Report on the regulation CD4+T Lymphocytes differentiation controlled by Regulatory T Cells, in vitro and in vivo in mice. Especially, at epigenetic level by the histone methyltransferse SUV39H1.Functions: -Purification of various immune cells: CD4+ T Lymphocytes, Regulatory T Cells, Antigen-Presenting Cells-Routine tasks: medium preparations, cell culture, cell labelling, production and purification of monoclonal antibodies-Analysis through flow cytometry