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On the 12th of February, we welcomed Ziqi Kang (PhD student, Färkkilä Lab, University of Helsinki) for an online guest talk on quantitative spatial analysis of the tumor microenvironment in high-grade serous ovarian cancer.

For our 2026 group retreat, the entire team gathered at Bildungshaus Kloster Schöntal 03–05 February. Set in the beautiful monastery surroundings, the retreat gave us dedicated time to discuss organizational topics, exchange ideas on science, and deepen our understanding of our wide range of research areas.

We hosted Dr. Marius Herr from the University of Tübingen, who presented FLAME — Federated Learning and Analyses in Medicine, a platform developed within the privateAIM initiative. He outlined how patient data can be analyzed in a privacy-preserving manner and demonstrated how our methods could be applied to clinical data through FLAME.

Azza joins our ML sub-team as a doctoral researcher working on uncertainty quantification and estimation for trustworthy AI. She brings experience in applied machine learning and language model engineering and will support our ongoing research on reliable ML methods in oncology.

This work presents Spectral Uncertainty, a new way to decompose uncertainty in large language models. Using the Von Neumann entropy, the method distinguishes aleatoric from epistemic uncertainty and incorporates detailed semantic structure in model outputs.

A proud moment: Florian has been listed as a Highly Cited Researcher 2025, placing him among the top 1% of scientists worldwide. This recognition reflects the shared work, ideas, and energy that move our lab forward every day.

Rashika joins the MLO Lab as a doctoral researcher working on probabilistic machine learning for multi-omic data integration and foundation-model approaches for single-cell representation learning. She will contribute to our research on machine learning methods for cancer data analysis.

Hendrik joins our ML sub-team, working on machine learning methods that combine large-scale EHR data with other data types such as genomics. He focuses on causality and uncertainty estimation and will support our ongoing methodological work.

Leo joins our group as a shared doctoral researcher working on the integration and interpretation of spatial transcriptomics and spatial proteomics data. Their research focuses on spatial multi-omics analyses to study immunotherapy effects in glioblastoma.

Yussuf joins our bioinformatics sub-team as a doctoral researcher working on interpretable probabilistic machine learning models for multimodal data integration. He applies these methods to projects on novel mRNA technologies for colorectal and pancreatic cancer and will support our ongoing research efforts.