Virginie
UHLMANN
Assistant Professor in Bioimaging and Data Analysis
BioVisionCenter Director
University of Zürich, Switzerland
Microscopy image analysis
My research group focuses on the development of novel algorithms to quantify complex visual phenotypes from microscopy data and on the application of these methods to biological discovery. Our contributions span both modality- and scale-agnostic image quantification methods leveraging state-of-the-art machine learning, as well as tailored computational pipelines developed through collaborative projects with experimental biologists.
We are currently
I
Investigating the design of invariant representation learning models to extract low-dimensional descriptions of complex geometries
II
Exploring the development of deep learning models to extract rich latent representations of visual information over multiple microscopy modalities and imaging scales
III
Investigating AI model adaptation in microscopy imaging to identify model mismatches and guide fine-tuning decisions
IV
Exploring the development of generative models of cellular morphotypes to test the extent to which morphological features recapitulate known biological classifications
Five Main Publications
ShapeEmbed: a self-supervised learning framework for 2D contour quantification
A. Foix Romero, C. Russell, A. Krull, V. Uhlmann, 39th Annual Conference on Neural Information Processing Systems (NeurIPS), 2025.
bia-binder: A web-native cloud compute service for the bioimage analysis community
C. T. Russell, J.-M. Burel, A. Athar, S. Li, U. Sarkans, J. Swedlow, A. Brazma, M. Hartley, V. Uhlmann, Bioinformatics, 41(8), btaf412, 2025.
ANCHOR: A Technical Approach to Monitor Single-Copy Locus Localization in Planta
D. Fabrèges, B. Corominas-Murtra, …, V. Uhlmann, E. Hannezo, T. Hiiragi, Science, 386(6718), eadh1145, 2024.
Simulating structurally variable nuclear pore complexes for microscopy
M. Theiss, J.-K. Hériché, C. Russell, D. Helekal, A. Soppitt, J. Ries, J. Ellenberg, A. Brazma, V. Uhlmann, Bioinformatics, 39(10), btad587, 2023
MorphoFeatures: unsupervised exploration of cell types, tissues and organs in volume electron microscopy
V. Zinchenko, J. Hugger, V. Uhlmann, D. Arendt, A. Kreshuk, eLife, 12, e80918, 2023