I’m a software and AI engineer with a PhD in Computer Science and 15+ years of experience in AI-related projects. My background is in applied AI and software engineering research for large-scale industrial software systems.

Professional Background

• Currently at CodeLaser.io as Principal Software Engineer, working on large-scale LLM-based software modernization
• Previously Head of AI at Oqton, leading deep learning work for 2D and 3D computer vision in additive manufacturing
• Former Tech Lead of the Data and Artificial Intelligence Competence Lab at Sirris, Belgium’s collective research center for the technology industry, where I led industrial R&D projects applying AI for predictive modeling, production optimization, and product usage monitoring.
• Postdoctoral work at ASML on advanced code analysis algorithms for migrating their software toward aspect-oriented modularization.

R&D and Funding Experience

Throughout my career, I’ve been involved in writing, executing, and managing R&D projects at both national and European level. I also serve as an expert reviewer for VLAIO, where I evaluate R&D proposals — primarily in AI, software, and industrial technology domains.

This combination of technical work, project execution, and proposal evaluation has given me insight into what makes R&D proposals succeed or fail — not just in theory, but in practice.

On this website, I share practical observations from working at the intersection of AI, software engineering, and applied research. The content reflects what I’ve learned from reviewing many proposals that never made it past evaluation.

This article highlights aspects of problem statements that I find crucial for a convincing R&D proposal. A strong proposal starts with a concrete customer problem, not a technology looking for an application. From a my perspective as a reviewer, the critical questions are: what problem are you solving, why does it matter, and why is AI specifically the right tool to address it?

For a broader view of how evaluators judge AI and R&D proposals, see my evaluation guide. .

This article provides an overview of the topics I evaluate critically in an R&D proposal as a reviewer. It explains at a high level why each topic is important and links to other articles that provide more details. Each of these detailed articles focuses on specific questions I typically ask, the patterns that raise concerns, and what distinguishes proposals that get funded from those that don’t.

By understanding these topics, why they are imporant, and the questions they trigger, you can better anticipate feedback and significantly improve the quality and credibility of your proposal.

This article is about selecting the right external partner to help you write a VLAIO funding proposal. It shares practical tips to help you understand what an external proposal writer can and cannot do, what input you must provide yourself, and how to assess a partner’s suitability for your project, your business, and the funding program. I believe following these guidelines increases your chances of ending up with a concrete, credible proposal with a higher likelihood of acceptance.

Based on lessons learned across multiple AI innovation projects, this article describes practical characteristics of a strong AI partner and a well-structured collaboration. They can be used as a checklist when developing an R&D funding proposal and help increase the likelihood of your proposal being accepted.