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Andreas Windisch

Head of Research Group

JOANNEUM RESEARCH

Andreas is a theoretical physicist and AI researcher. After earning his doctorate sub auspiciis praesidentis in Graz and working as a Schrödinger Fellow at Washington University in St. Louis, he returned to Austria to lead the Intelligent Vision Applications group at JOANNEUM RESEARCH. He serves as Chief Science Officer at AI Austria, teaches AI at FH JOANNEUM, and mentors start-ups at ESA’s Science Park Graz. His work focuses on computer vision and multimodal AI systems in fields such as space, health, media, and quality assurance. He also coordinates AI efforts at JOANNEUM RESEARCH and advises Austria’s AI strategy as part of the national Stakeholder Forum.

What does innovation mean to you?

Innovation, to me, is not necessarily the invention of something new. There are many clever ideas out there, but very few stand the test of time when it comes to creating value. Innovation is what enables this transition, it is the means by which an idea becomes real enough to create value.

What do you believe is the most important capability for companies to thrive in the economy of tomorrow?

Borrowing a concept that is usually applied at the individual level, I would say it is 'thinking on your feet'. The ability to adapt quickly, to remain flexible, to learn continuosly, and to course-correct in a rapdiyl changing environment. Ultimately, the companies that will thrive tomorrow are those that have learned how to cope with today.

How can we leverage our collective strength to create a more prosperous future?

Austria has all the relevant ingredients: strong research institutions, capable industries, and a growing startup ecosystem. The real opportunity lies in connecting these elements deliberately, to share knowledge, to align incentives, to bridge gaps between disciplines. This is how isolated excellence turns into systemic impact.

Describe your project and work and what makes it so innovative?

My research group develops AI-driven solutions that help organizations make better decisions and operate more efficiently. What makes this work innovative is the consistent focus on impact: not just building models, but ensuring they integrate into workflows, scale across use cases, and deliver measurable value. Innovation, in this context, means moving beyond prototypes to systems that actually change how organizations operate.

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