Computer Vision News - October 2021

50 Women in Science Best of MICCAI 2021 Sometimes we have different ideas. You told us only half of the story - the half of the story about the research you are doing. I know that you are also teaching. Can you tell us a little bit about the second part of the story? It’s funny because I just came out of a meeting to prepare for the next course on machine learning that starts in two weeks. At the moment, we have more than 300 students in this course. As you can imagine, it has changed from 50 students ten years ago to 300 now. A lot of people are interested in these topics. We have to let them know, for example, about these recent deep learning models that everyone is hearing about. We have to contextualize these for the students. That’s mainly what I do. I teach machine learning at the university. I also supervise students. I supervise several Master’s students in different computer vision topics and in robotics as well, mostly using machine learning. We try to challenge them to use recent methods. You have supervised more female students than male students. How did this come about? To be honest, I don’t know. I don’t know if it’s because I am a female supervisor. Sometimes I know that it plays a role, although my PhD and Master’s supervisor was male. We share the students sometimes. What is changing is the way women approach engineering. When I took the machine learning course 10 years ago… no 11 years ago, there were six female students out of about 60 students. It’s less than one tenth of the students. Now, we have “We are just one piece of this puzzle…”