Vincent Bürgin

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Hi, I’m Vincent! I’m a computer science generalist interested in a wide range of things.

I recently graduated from the M.Sc. Informatics program at the Technical University of Munich (TUM). In the last years, I had the chance to be involved in a number of research projects in the machine learning and medical imaging fields (in the TUM DI-LAB at the CAMP chair, at the Theoretical Foundations of AI chair, at ImFusion, and at the Lab for AI in Medicine), and several projects led to published papers.

I also have a passion for mathematics, and completed a B.Sc. in Mathematics alongside my B.Sc. in Computer Science at the University of Passau. I like to work somewhere close to the border between computer science and mathematics, such as with my Master’s thesis, which explored a topological loss functions rooted in persistent homology, and my Bachelor’s thesis, which was about the properties of a particular stochastic order and whether or not it can be used for game theory.

I’ve worked with a variety of programming languages and technologies, and I’m always keen to learn new ones. Python is my go-to language for machine learning and most day-to-day coding needs. More recently I’ve began to use more C++, and of course I love Rust and try to find a reason to use it whenever I can. I’m also using JavaScript for interactive visualizations and creative coding, and have used C# for a lot of different projects before I started my studies. I’ve also used Haskell, Julia and several other languages in projects.

news

publications

  1. Topologically faithful multi-class segmentation in medical images
    Alexander H Berger, Nico Stucki, Laurin Lux, Vincent Bürgin, Suprosanna Shit, Anna Banaszak, Daniel Rueckert, Ulrich Bauer, and Johannes C. Paetzold
    Medical Image Computing and Computer Assisted Intervention (MICCAI), 2024
  2. Efficient Betti Matching Enables Topology-Aware 3D Segmentation via Persistent Homology
    Nico Stucki, Vincent Bürgin, Johannes C. Paetzold, and Ulrich Bauer
    arXiv preprint: arXiv:2407.04683, 2024
  3. Robust vertebra identification using simultaneous node and edge predicting Graph Neural Networks
    Vincent Bürgin, Raphael Prevost, and Marijn F. Stollenga
    In International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2023
  4. S3M: scalable statistical shape modeling through unsupervised correspondences
    Lennart Bastian*, Alexander Baumann*, Emily Hoppe, Vincent Bürgin, Ha Young Kim, Mahdi Saleh, Benjamin Busam, and Nassir Navab
    In International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2023
  5. On the Localization of Ultrasound Image Slices Within Point Distribution Models
    Lennart Bastian*Vincent Bürgin*, Ha Young Kim*, Alexander Baumann, Benjamin Busam, Mahdi Saleh, and Nassir Navab
    In International Workshop on Shape in Medical Imaging, 2023
  6. Remarks on the tail order on moment sequences
    Vincent Bürgin, Jeremias Epperlein, and Fabian Wirth
    Journal of Mathematical Analysis and Applications, 2022