As Q, Matthias focuses on pushing technical innovation at ML6 and guaranteeing that our customers benefit from the latest technical advancements.
This means constantly improving the chapter working, as well as providing clear links to customer projects and making sure that ML6 has the right technological partnerships to maximize customer impact.
Matthias is energized by coaching technical talent, internally, but also the wider ML ecosystem. He is cofounder & organizer of multiple meetups and frequently acts as technical advisor for startups and colleges/universities.
He's also a trusted expert adviser for the Flemish Agency for Innovation and Entrepreneurship to provide insights and review research projects.
He started his career as PhD researcher at Ghent University focusing on the development of novel event extraction algorithms based on deep learning techniques. Having gained expertise in this new and upcoming technology as well as user testing/evaluation, he was convinced of the immediate opportunities in the industry and prematurely stopped his PhD to join Nicolas in the early days of ML6. This passion led Matthias to become Google Developer Experts for GCP and one of the first GDEs for Machine Learning.
What do we do though if we don’t have any or enough usable data yet to get started? One obvious option is to collect (more) data. However, today we want to go beyond that. We will look at three other dimensions that can be relevant to unblock ML use cases: data protection, external data, and synthetic data.
September 6, 2022