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With companies increasingly turning to AI and data to grow their business, the need for ‘real-life’ data-science expertise grows. Paul Groth leads the team at the Intelligent Data Engineering Lab (INDELab). “We know how to work with you,” he says. “Our team has experience with industry, really strong experience looking at real-world issues and being inspired by them.”

Can you give us an introduction to what you do?

I’m a professor of data science, and I wear multiple different hats. I lead the INDELab, where we apply AI to the problems of how people work with data. Concretely that means things like: how do we automatically build great quality datasets from various sources, including text and structured data, or even images and videos? Another focus area is data management for machine learning: researching how we can help data scientists or AI engineers make their machine learning better. Things like: how do we check the quality of data? How do we help people debug their data science or AI pipelines? With another hat on, I’m co-scientific director of two ICAI labs [Innovation Center for Artificial Intelligence]. The AIRLab, in partnership with Ahold-Delhaize, and the Discovery Lab with Elsevier.

I’m also scientific director of the University of Amsterdam’s data science centre. That’s a really exciting thing – it’s designed to help us use data science or AI techniques to accelerate our research in all the faculties. Whether you’re in the humanities or law or life sciences, we ask: how do we make our research better, faster, higher quality, by injecting AI and data throughout all of it? I also teach in our information studies programme.

Read the entire interview on the Amsterdam Science Park website.