AI Consulting
AI Scientific Consulting
Since 2026, I provide strategic and technical AI consulting for scientific and engineering organisations, with a focus on translating frontier AI methods into practical, validated systems.
Areas of Expertise
Machine Learning for Scientific Applications
Designing, validating, and deploying ML systems for complex scientific datasets — including feature engineering from sensor data, longitudinal modelling, and model validation frameworks suited to regulated environments.
Agentic & Generative AI
Designing autonomous AI pipelines for scientific workflows: Retrieval-Augmented Generation (RAG), Model Context Protocol (MCP) integrations, and LLM-orchestrated research automation. Finalist, Oxford Clinical AI Hackathon — Agentic AI Communication Challenge (2026).
Digital Health & Medical AI
End-to-end expertise in digital biomarker development — from sensor data collection and processing, through model development, to regulatory-aware validation. Experience with FDA-adjacent medical device development contexts.
Reproducible & Production-Ready ML
Building ML systems that hold up: monitoring, drift detection, testing frameworks, FAIR data practices, and documentation standards for scientific and engineering applications.
Selected Engagements
Kneumhealth (2026–present)
Oxford Neurology medical spinout. I support the integration of research-grade digital biomarkers into their clinical innovation product, and help establish a long-term agentic AI strategy across their multiple sensor platforms and data pipelines. FDA-regulated development context.
Additional confidential engagements in scientific and engineering sectors.
Enquiries
Open to project-based consulting engagements, advisory roles, and collaborative partnerships at the interface of AI and science, medicine, or engineering.
📧 timothee.aubourg@gmail.com
🔗 LinkedIn