Consulting
I advise MedTech teams on technical and data-driven decision-making in computer vision projects, from early research questions to applied R&D and validation.
With a PhD in Computer Vision and over ten years of experience leading applied research and development in MedTech, I bring perspective on experiment design, data assumptions, and technical feasibility throughout the R&D lifecycle.
My work focuses on ensuring that technical choices, data assumptions, and evaluation strategies are aligned with real-world constraints, so that R&D efforts lead to robust and credible outcomes.
How I Work
I collaborate with MedTech teams through technical advisory, either via focused interventions or sustained follow-up over the course of an R&D project.
Some engagements focus on a specific question or phase, such as feasibility assessment, data readiness evaluation, experiment design, technical review, or validation strategy. Others take the form of longer-term collaborations, where I follow the project over time and contribute regular input as technical choices evolve.
My involvement adapts to the project’s rhythm: from punctual reviews to regular advisory exchanges, always with the aim of supporting sound technical decision-making throughout the R&D lifecycle.
Where I Intervene
My consulting work strengthens the AI R&D lifecycle from early framing to long-term technical defensibility.
I intervene across key phases of the AI R&D.
1. Technical Framing & Feasibility
When teams need to clarify problem formulation, technical scope, or feasibility at early or intermediate stages of an AI project, including objectives, constraints, available data, and key risks shaping downstream decisions.
2. Data & Project Readiness
When teams want to assess data, infrastructure, and project setup to identify gaps, risks, or misalignments affecting model development, validation, or future deployment.
3. Experiment Design & Evaluation Strategy
When experiment design, evaluation protocols, or benchmarking approaches need to be defined or reviewed to ensure results are interpretable, comparable, and aligned with real-world use cases.
4. State-of-the-Art Review & Technical Positioning
When targeted scientific and technical reviews are needed to identify relevant methods, tools, and approaches for a given use case, and to support informed and defensible technical choices.
5. Ongoing Advisory and Due Diligence
When an independent technical review of existing systems, models, or documentation is needed to support internal decision-making, partnerships, or investment discussions, with the option of ongoing advisory support as projects evolve.
Who I Work With
- MedTech startups and scaleups developing AI-based products
- Healthcare and medical imaging teams advancing AI initiatives
- Technical and executive leaders seeking an external sparring partner on AI strategy and R&D decisions
Key Benefits for Your Organization
- Clear technical decision-making
- More meaningful experiments
- Reduced downstream risk
- Credible technical positioning
- Continuity of judgement
Why work with me?
- Deep Technical Authority
PhD-level expertise in computer vision, combined with over ten years of experience leading applied R&D in MedTech environments. - Experience at the R&D-Reality Interface
Long-term involvement in projects where research constraints, data realities, and real-world requirements must align. - Independent and Structured Perspective
Acting as an external technical reference, bringing clarity, rigor, and structure to complex technical discussions. - Decision-Oriented Communication
Translation of complex technical topics into clear, decision-ready insight for technical leaders, executives, and non-technical stakeholders alike. - International and Bilingual Context
Fluency in English and French, with experience working across academic, clinical, and industrial settings.
Working on an AI project?
Let’s define a sound technical approach for your next decision.
