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  • Expression of Interest

    University of Warsaw

    High-throughput genomic technologies (RNA-seq, single cell isolations, spatial transcriptomics, and more) collect an ever-increasing amount of data about model organisms and humans. To facilitate data-driven discoveries in biology and medicine, my team develop machine learning methods, particularly focusing on unsupervised methods ranging from PCA-like appraoches to variational auto-encoders, for large-scale experimental and observational studies. We are interested in identifying underlying signatures of diseases, molecular pathways, and environmental factors by decomposing systematic patterns of variation. Our recent methodological works have been related to latent variable models (e.g., factor analysis) and unsupervised deep learning (e.g., variational autoencoders) among others. These approaches have yielded high impact projects in fundamental molecular biology such as understanding cell cycles in yeasts and dissecting cellular identities in single cell RNA-seq, as well as in translational research involving cardiovascular diseases, malaria parasites, and other complex phenotypes.


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    The University of Warsaw is the top-ranked institution of higher education in Poland. Our Institute of Informatics has been particularly renowed for its theoretical and practical computer science evident by our graduates being hired at premier tech companies. We further have a focus group in computational biology, where we closely collaborate with top biologists and clinicians around the world.