About

I am currently studying Data Science & Biomedical Engineering at Mines Saint-Étienne.

My academic background combines statistics, machine learning and computational biology, with a focus on genomics and drug discovery.

My medical background includes coursework in physiology, anatomy, pathology and pharmacology.

My research experience sits at the intersection of machine learning, mathematical modelling and the human microbiome.

During my research internship in the Department of Bioengineering at Imperial College London, I worked in computational systems medicine, using generalised Lotka-Volterra models, Bayesian inference and hierarchical modelling to infer microbial interactions from human skin microbiome data.

I am now continuing at Imperial for my Master project, applying machine learning methods (SVM, Random Forest, logistic regression) to identify the core bacteria involved in atopic dermatitis.

Before moving into engineering, I completed a Bachelor in Medicine at the Université Catholique de Louvain, covering molecular and cellular biology, genetics, cardiology and anatomy.

At Kaohsiung Medical University in Taiwan, I observed clinics, surgery and patient cases in cardiology and general internal medicine. This clinical background shapes how I approach biomedical data today.

Programming
Python, NumPy, Pandas, PyTorch, scikit-learn, Git

Languages
French · Native
English · Fluent · C2 Proficiency Exam
Spanish · Basic