Florian Ingelfinger's research locates at the intersection of immunology, neurology, and computational biology. During his PhD with Burkhard Becher at the University of Zurich, he applied advanced single-cell methodologies to investigate immune communication networks in autoimmunity and inflammation. His work identified pathogenic T cells in Myasthenia gravis, highlighted therapy impacts on patient risks, and dissected the impact of genetics and environmental factors on the immune profiles of multiple sclerosis patients. In his postdoctoral research with Ido Amit and Nir Yosef, he co-developed Zman-seq, a novel technique for tracking cellular transitions across time using single-cell transcriptomics. Using a combination of temporal in-vivo labeling and spatially-resolved single cell transcriptomics he provided a novel perspective on leukocyte infiltration into the tumor immune microenvironment. Moreover, Florian Ingelfinger developed CytoVI, a generative deep probabilistic model to circumvent current limitations of antibody-based single cell technologies, such as flow cytometry, mass cytometry or CITE-seq. CytoVI seamlessly integrates antibody-based data across different panels and technologies, effectively removing technical variation while enabling the imputation of unmeasured markers and modalities. Demonstrated to reliably predict patient outcomes, CytoVI stands as a powerful tool for both preclinical research and automated clinical analysis.