Zuzana Kukelova Daily MONDAY 10 Zuzana Kukelova is an Assistant Professor at the Czech Technical University in Prague. Zuzana, can you tell us about your work? I am working mostly in applications of algebraic geometry in computer vision. This involves efficient solving of systems of polynomial equations for computer vision problems. Such problems appear in many different applications like 3D reconstruction, camera calibrations, robotics, also in localization, everywhere you have systems of polynomial equations, and you need to solve these systems of polynomial equations really efficiently. Why did you choose this field? I was studying math for my Master’s. When I started my Ph.D., Gröbner basis method appeared in computer vision. It is not really complicated math, but I think people from computer vision community were slightly afraid of this pure math. I started with this topic. I realized that I could apply this method to many other computer vision problems. When did you discover that you were good at math? My father was a math teacher. I was attending all of these math competitions in primary school. Did you win? I was usually in the top 10%. Did you have good math teachers? Yes, yes… I was studying in Slovakia. Also, in university, we had really good math teachers. Where in Slovakia? In Bratislava. Can you tell us what you learned the most from your teachers? I can’t think of one thing, but I really liked the style of teaching they had, e.g. I didn't need to read any book during my studies because everything was really clear from these lectures. You originally from Slovakia and now you are teaching in the Czech Republic. What is the story? The story is that I moved to the Czech Republic for my PhD studies. We have a similar language and culture. For me, it was really easy to continue my studies there, and I got a really nice offer in this country at the Czech Technical University. Unfortunately, we don’t have so many opportunities in Slovakia, especially in computer vision. It was not possible to study computer Women in Computer Vision 16

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