His research focuses on visual inductive priors for deep learning for automatic image and video understanding. He published over 75 peer-reviewed papers with more than 5,000 citations.

‘Computer Vision’ is teaching a computer to recognize images and video. Nowadays this is mainly done through ‘deep learning’ a form of artificial neural networks that allow a computer to learn from unstructured input such as images. Jan specifically does research on how to add knowledge to deep networks to learn more efficiently, requiring less input data.

Jan: “I find it amazing to ask good research questions, doing cutting edge research applied to practical applications. Unbridled creativity and unlimited freedom drew me to computer science. Especially artificial intelligence is fascinating: thinking about how to make a computer think. Visual data is especially captivating as they are so easily interpreted by humans, but are so difficult to understand by a machine. It gives me respect for what the human brain can do.”