SCAI – Sorbonne Center for Artificial Intelligence

SCAI – Sorbonne Center for Artificial Intelligence

Head of Data Science · Jan 2025 – 2026 · Paris

I led a team of 4 data scientists and research engineers, building AI and data science solutions for researchers across Sorbonne University’s three faculties and its national and international partners.

Team & Collaborations

• Skills: computer vision, NLP, large language models
• French lab partners: iEES, LPSM, SUMMIT, AP-HP, IPSL, LIMICS, ISIR, Observatoire Océanologique de Banyuls, IRD, ANSES, Institut Pasteur, INRIA
• International: Université Laval (Québec), Sorbonne Abu Dhabi, Sémé City (Bénin)
• Part of two France 2030-funded programs: Sorbonne.AI (education & PhD) and PostGenAI@Paris (national research cluster)

Selected Projects

• 🎨 Digital Delacroix — Computer vision for art history, with Centre André-Chastel and the Assemblée Nationale
• 🌍 Cowspiracy — Animal detection models for soil erosion monitoring in Senegal & the Gobi Desert, with iEES Paris and IRD
• 🧪 Annotix — Graph ML and molecular networking to annotate unknown molecules from MS/MS spectra, with Observatoire Océanologique de Banyuls
• 🤖 Sorbobot — LLM-based expertise mapping across Sorbonne University, with SUMMIT engineering teams

Grant & Funding Support

• 15+ responses to competitive calls for projects (ANR, France 2030, etc.) · 6 accepted, each funding a 1–3 year data scientist position

Internship Supervision

• 10 Bachelor’s and Master’s internships applying AI to chemistry, biology, medicine, and humanities

Research Engineer / Data Scientist · Apr 2023 – Dec 2024 · Paris

Implemented collaborative ML and data science projects with Sorbonne researchers across NLP, computer vision, and medical applications. Contributed to the SCAI Education platform and delivered courses for Bachelor’s students at UFR de Mathématiques.

Training & Education (2023–2026)

• Personal: 230+ hours · 300+ students · 10+ courses
• Team total: 400+ hours · 700+ students · 40+ courses
• Audiences: medicine, humanities, physics/maths, innovation management, continuing education
• 2 programs delivered in Sorbonne Abu Dhabi (continuing education)
• Developed a no-code AI literacy workshop for non-technical audiences: data, ML models, training and inference

Lecturer in Python and Machine Learning · Dec 2022 – Apr 2023 · Paris

Contributed to the Sorbonne.AI education program for Bachelor, Master and Continuing education.

Selected courses:

• ISUP – Ingénierie Statistique et Data Science (30h): Python fundamentals, OOP, packaging and clean code, scientific computing and ML
• UFR Ingénierie Mathématique (12h): Python fundamentals, OOP, data visualization
• Medicine School: Introduction to Python coding and Machine Learning for data analysis, course and workshop

Freelance

Senior / Lead Data Scientist · Sep 2022 – Mar 2023

Supported companies on their ML projects: defining R&D roadmaps, leading data science teams, implementing and deploying ML systems. Including a computer vision mission at Tabobine (defect detection and image quality analysis).

LumenAI

CTO & Head of Data · Nov 2020 – May 2022 · Paris & Tours

LumenAI is a data science consultancy and R&D company. Led the full technical team of 6 people (data scientists, ML researchers, data engineers), fully remote across Paris, Rennes, and Pau.

• R&D — Cybersecurity: Real-time network intrusion detection using graph clustering, funded by the DGA Cyberdefence Factory program (Rennes). Delivered a working prototype.
• Consulting — TotalEnergies (Pau): Built a large-scale document indexing and search system over a very large internal text corpus, using NLP and online clustering. Signal processing and smoothing applied to geoscience sensor data using computer vision models.
• Research: Co-supervised a PhD student · co-author of 1 research article.

Safety Line

Head of Data Science · 2017 – 2020 · Paris

Safety Line provides data-driven solutions for aviation efficiency and safety to airlines and airports worldwide. Led a team of 5 data scientists and engineers in a start-up environment (~50% management, 50% hands-on technical).

• Aircraft fuel consumption optimization, airports analytics and emissions reporting for 10–20 airline clients
• Large-scale processing of flight data recorder streams (1,000+ parameters per second)
• Academic partners: INRIA, LIP6 (Sorbonne), IFSTTAR
• Industrial partners: Aéroports de Paris (ADP), Thales (European research project)
• Co-supervised a PhD student with INRIA on dynamical system identification and optimal control (2015–2018)
• Co-author of 4 peer-reviewed research articles and 2 patents

Key Achievement: Oversaw the design and delivery of a fully automated ML pipeline — from raw flight data decoding to Dockerized production deployment.

Machine Learning Scientist · 2015 – 2017 · Paris

Large-scale flight data processing and ML algorithm design for aircraft fuel consumption reduction.

Key Achievement: Designed and implemented ML algorithms and Python APIs for climb phase fuel optimization — delivering up to 10% fuel savings per flight.

PhD Candidate in Statistical Learning · 2011 – 2015 · Paris

Random Forests and variable selection – Analysis of flight data recorders for aviation safety. With Université Pierre et Marie Curie (CIFRE).

Key Achievement: Two publications in international journals (variable selection and functional data analysis), one French patent, and one R package.

Publications & Patents

→ Full list of publications

• 8 peer-reviewed research articles
• 2 patents

Teaching

→ Full teaching record

• 230+ personal teaching hours · 300+ students
• 10+ courses across Bachelor’s, Master’s, and continuing education