Our lab operates at the interface of computer science and developmental biology. We focus on the development of computational methods for analysing morphogenesis at the single-cell scale in whole organisms throughout their development.

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Our primary objective is to apply computer vision, graph-based, machine learning and big data algorithms to quantify and comprehend developmental reproducibility during embryogenesis in various model organisms.

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Our ultimate aim is to investigate the impact of developmental variability on morphogenesis by utilising homemade statistical averages from two main data modalities: fluorescence microscopy images and spatial omics.