01 / MEDICAL AI · LEADERSHIP
Dermascan
From a triage model to tools used in the field.
Leading AI engineering, connecting images and clinical data, and integrating models into medical workflows.
Read the case study →RESEARCH · ENGINEERING · TEACHING
Arthur Cartel
Foahom Gouabou
Lead AI Engineer · PhD
I turn complex AI problems into usable systems: medical computer vision, generative AI and production deployment.
Lead AI Engineer at Dermascan. PhD in Computer Science, based in Marseille.
- 100,000+
- Lesions analysedDermascan · 6 centres
- +10%
- Operational efficiencyDMSLOG.ai · logistics
- 11
- Scientific publicationsMedical vision & applied AI
- 140
- Scientific citationsGoogle Scholar
- 100+
- MLOps learnersTraining · Alphorm
FROM RESEARCH TO REAL-WORLD USE
AI does not stop at the model.
My work connects research, business needs and engineering: designing an approach, building the tools that make it usable and supporting the teams who use it.
Three domains. One connecting thread.
Industry and research contributions, with my role, technical approaches and available evidence.
02 / LOGISTICS · APPLIED AI
DMSLOG.ai
Making logistics data searchable and predictable.
Flow forecasting, RAG-based KPI queries and document extraction for container logistics.
Read the case study →03 / RESEARCH · MEDICAL VISION
DIAMELEX & medical vision
Studying model limitations, not just their scores.
Research into skin lesion classification, class imbalance and explainability, with publications and code.
Read the case study →What I bring to your team.
Design & evaluate
Computer vision, class imbalance and model evaluation. Research connected to the constraints of medical imaging.
Explore the research →Build & deploy
OCR + LLM pipelines, RAG, APIs and MLOps. Connecting data to use cases and production tools.
Explore the logistics case →Lead & teach
Architecture, technical reviews, cross-functional collaboration, MLOps training and mentoring.
Explore training →Two ways to work together.
You are hiring
Looking for someone who connects applied research, technical leadership and AI delivery? Explore my background, responsibilities and contributions.
Discuss an opportunity →You are building or training a team
Let’s discuss applied AI, technical support or MLOps training. Scope and availability will be defined together.
Discuss a collaboration →Scientific rigour, with sources you can explore.
Publications in medical vision and logistics forecasting; articles and code to understand the methods beyond a list of technologies.
A role to fill. A problem to solve. A team to develop.
Tell me about your context, objectives and key constraints.
Get in touch