I am currently a PhD student in Martin Weigert’s group at EPFL in Switzerland, where I develop machine-learning-based methods for analysing microscopy images of the building blocks of life.

Proteins, organelles, cells, tissues or even entire animals; to learn about them we can often simply take a (sophisticated) picture or video. And after that we need to extract quantitative information from our recordings!

While supervised deep learning is enjoying a lot of success for processing bioimages, it is often limited by a lack of appropriate ground truth annotations. How can we incorporate uncurated images fresh off the microscope into training neural networks?

If you are excited about this as well please reach out :)

Previously, I have worked on automating cell organelle segmentation in electron microscopy data in Tom Kirchhausen’s lab at Harvard Medical School, as well as on 3D neuron reconstruction from electron microscopy in Jan Funke’s group at HHMI Janelia.

Teaching:

• Bioimage Informatics @ EPF Lausanne (2022, 2023)
• Deep Learning for Microscopy Image Analysis @ MBL Woods Hole (2022)
• Deep Learning for Image Analysis @ EMBL Heidelberg (2022)
• Image Processing 1 @ EPF Lausanne (2022)
• Natural Language Understanding @ ETH Zürich (2018, 2019)
• Advanced Machine Learning @ ETH Zürich (2017)