Wouter Favoreel

The goal of Flanders Make is to support companies in their Industry 4.0 and 5.0 transition, in order to improve their competitive position in the global economy. In this role I help capture the needs from manufacturing companies and translate these into a sector and project road map. These projects are always a close collaboration between the companies and Flanders make engineers and researchers. Feel free to check out our video channel if you want to know more about the cool stuff we work on: https://lnkd.in/eY8NxiK7

The goal of Flanders Make is to support companies in their Industry 4.0 and 5.0 transition, in order to improve their competitive position in the global economy. In this role I help capture the production needs from companies and translate these into a technology project road map. These projects are always a close collaboration between the companies and Flanders make engineers and researchers. Feel free to check out our video channel if you want to know more about the cool stuff we work on: https://lnkd.in/eY8NxiK7

I am an enthusiastic engineering manager with 10+ years of experience in leading multi-disciplinary and multi-site teams. I love tackling challenging high-tech projects where machine learning and cloud technology are key components. I find it very inspiring to work for a company with a clear vision and products / services that try to make the world a better place. Although I know the drills of large public companies, I prefer the let’s-do-this-together spirit of a startup. Feel free to check https://www.flir.eu/traffic if you want to know more on some of the projects I worked on.

After the acquisition of Traficon by FLIR, I had the opportunity to lead the entire engineering team of the Traffic business unit. In this role, I reported to the General Manager of the Traffic BU. Together with the Product Managers and the other members of the Management Team, we defined the vision, strategy and product road map for all traffic products. For more background on these great products, feel free to check https://www.flir.eu/traffic. As engineering lead, I was responsible for multi-site and multi-disciplinary teams of in total 35 engineers and all operational aspects of these teams. The core competences of the people were Machine Learning / AI, full stack development and cloud integration, firmware development (C++), mechanical and electrical design, product compliance, QA and industrialization. Several aspects of our work, and way of working, were recognized and deployed across the entire FLIR engineering group. Due to this, we won the 2020 FLIR Innovation Award, which is something we were really proud of. After the acquisition of FLIR by Teledyne in 2021, I became responsible for the operational aspects of the site in Marke (Belgium).

Traficon was an SME based in Kortrijk (Belgium), focusing on the development and world-wide commercialization of smart cameras for road traffic applications. The purpose of these cameras was to make traffic safer and more efficient. Typical applications were automatic tunnel surveillance and signalized intersection control. Traficon was acquired by FLIR in 2012. In the role of Innovations Manager, I was responsible to search, initiate and follow-up on technology partnerships with companies and universities in order to make better products and reduce the time to market. Many of these projects were focusing on integration of 3rd party Machine Learning and AI technology into the Traficon products. I was also responsible to follow-up on funded R&D projects (Flanders, Belgium and EU) and patent applications.

Traficon was an SME based in Kortrijk (Belgium) focusing on the development and world-wide commercialization of smart cameras for road traffic applications. The main goal of these cameras was to make traffic safer and more efficient. Typical applications were automatic tunnel surveillance and signalized intersection control. Traficon was acquired by FLIR in 2012. In the role of R&D Engineer, I was responsible to research, develop and deploy the AI / Machine Learning algorithms for the various traffic applications. Since these algorithms had to be portable (C++) in the traffic cameras, limiting the memory and CPU foot print was paramount. The cameras were in many cases unsupervised and therefore had to operate 24/7 and with sufficient accuracy in challenging outdoor conditions.

PhD from the Department of Electrical Engineering at the Katholieke Universiteit Leuven, Belgium. Dissertation title: “Subspace methods for the identification and control of linear and bilinear systems”, supervisor: Prof. dr. ir. Bart De Moor.