— Experienced Data Scientist with a proven track record in developing innovative solutions driving significant revenue growth and substantial cost savings. — I’m a PhD specialized in Artificial Intelligence with a strong background in machine learning and computer vision. — Over the past few years, I’ve been working on advanced ML projects, including real-time document recognition and typing, where I combined text clustering, image classification, and perceptual similarity methods like Haar features. — I also developed object detection pipelines for video data, including a full workflow. These pipelines covered end-to-end processes from data preprocessing, model training, evaluation, to prototyping POCs. Key achievements: — Scoring system increasing revenue by 85% (from €305k to €564k, Portugal). — Document recognition system generating €250,000 in savings. — Key contribution: logistics restructuring (€1,000,000 annual savings and carbon footprint reduction). Publications: Research papers: — Generating Text from Anonymised Structures (2019), INLG Conference. — Generating Syntactic Paraphrases (2018), EMNLP Conference. — Robot Experience Stories (2018), Journal of Intelligent & Fuzzy Systems. — Création automatique d’une grammaire syntaxico-sémantique (2017), RECITAL Conference. — The WebNLG Challenge: Generating Text from DBPedia Data (2016), INLG Conference. Theses: — PhD Thesis: Deep Learning & Natural Language Processing (2020), University of Lorraine. — Master’s Thesis: Cerebellar Modeling (2015), INRIA.