Computer Vision News - January 2017

around 80 students in total. When did you decide to become a scientist and a teacher? [ laughs ] My mom is a teacher. That was always a career option for me. She was actually the math and physics teacher at my high school. Both of my parents are physicists so that always made a good career option for me. Well, we didn’t always talk about science at home, but certainly many little things at breakfast turned into math problems. It’s something I’d like to pass on to my daughters as well. That’s funny because I know people who want to be exactly the contrary of their parents. It’s nice to see someone who wants to follow in their footsteps. Are they still your role models? Well, they are not academics. They are scientists, I suppose. They both did a Master’s. My father did a PhD. Yes, I respect them for that, but becoming a scientist came quite late for me: after finishing high school, I went to university and did not know what to do [ laughs ]. Computer science at that time was a good option because it opened up many different avenues. It was only toward the end of my studies that I decided I wanted to learn more. Learning is something I always really enjoyed. Most days I enjoyed going to school. I don’t ever stop learning really. As an academic, I still learn things because I have to teach new things. I also learn from my students and my postdocs. Sometimes they teach me rather than me teaching them. What do you learn from your students? I’ve been an academic since 2007. I’ve learned a lot of patience and a lot of tolerance as well. I respect that they are all individuals. What works for one student doesn’t work for another student… like with my children. They’re all different, and they have different needs. Some students are like unsupervised neural networks: they go off on their own trajectory, and I just stand there and admire their process and progress. Others really need more help. That helps me to understand where their problems lie because when they get stuck, getting them to formulate the problem is part of understanding their thought process, and seeing it from their angle has always been very interesting for me. Your daughters are 13 and 11: was it difficult to balance your role as a mom with your role as an academic? Computer Vision News Women in Computer Vision 21 Women in Science “ As an academic, I still learn things because I have to teach new things. I also learn from my students and my postdocs. Sometimes they teach me rather than me teaching them ” “ Some students are like unsupervised neural networks: they go off on their own trajectory ”