Sarah Costa

Profile

Sarah Costa is a PhD student at the Zienkiewicz Institute for Modelling, Data, and AI. Her research focuses on developing innovative methodological frameworks leveraging computer vision and Machine Learning (ML) for the segmentation and dynamic analysis of microscopic imaging and video datasets obtained from laboratory networks of cardiac cells. By enabling the automated and localised acquisition of quantitative data from individual cells and the extraction of time-resolved information on cell-to-cell interactions within these networks, her project aims to facilitate the predictive modelling of cardiac functionality under physiological and pathological conditions. Sarah is passionate about advancing the fields of AI and ML to enhance cardiomyocyte dynamic network analysis.

Area of Experties

  • • ML for Cardiac Network Analysis
    • Computer Vision
    • Microscopic Images Segmentation
    • Molecular Cardiology & CVD

 


Projects

  • Enhancing Cardiomyocyte Dynamic Network Analysis with Machine Learning

    Enhancing Cardiomyocyte Dynamic Network Analysis with Machine Learning

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    Project Overview Cardiovascular disease (CVD) is the leading cause of morbidity and mortality worldwide,responsible for approximately 17.9 to 20.5 million deaths annually. Whilst the global burden of CVD keeps increasing, recent efforts to accelerate the development of innovative therapeutic strategies for managing CVD have persistently failed to deliver new drugs to the market. These challenges…

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