Lea Bogensperger is a postdoctoral researcher at the University of Zurich in Switzerland. Lea, what is your work about? I'm coming from a PhD in computer science. I worked mainly on inverse problems and image reconstruction, basically tackling different problems in the image acquisition pipeline from alignment and reconstruction to bi-level optimization and then also to segmentation. It was nice for me to see like a broad span in the vision pipeline. And now in my postdoc I transitioned a bit to work also on different kind of medical or biological data. For example, also proteins now but of course I’m still working with optimization and machine learning techniques. Is that what you wanted to do? What I always wanted to do is have some medical applications. I'm still also working on images, medical images from the hospital for example, but that is the most important thing to me. Do you have anything in your work experience that you can already claim as something that you are proud of? It's not near done yet but if that ever happens and I can contribute to that, I would be very proud of. It's an ongoing project. You have a paper here at WACW. I'm a co-author, yes, with a collaborator from Austria who's doing her PhD right now. Of all the things that you have done during your PhD, which one is the most useful for your current work? I think all of them helped me of course to develop my knowledge in the field. But I liked a lot my last project, where I worked on generative methods for image segmentation. I was segmenting microscopy images using diffusion models, so you can have it in a sort of probabilistic way. And I think the methods I learned there when I started my postdoc here in Zurich, I was kind of thrown into a completely different field of applications like protein sequences. But whatever I learned during my PhD on the images I could carry on so much to the proteins now. So I think methodologically you can have a lot of related things but then of course the challenge is to work with new data each time. Was your PhD worth doing? Oh of course, of course. In retrospect you will always say you'd Read 160 FASCINATING interviews with Women in Computer Vision Read 160 FASCINATING interviews with Women in Computer Vision Women in Computer Vision 12 DAILY WACV Monday
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