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Antoniya Georgieva has developed a career in biomedical research, specializing in machine learning and computational mathematics, particularly in the area of intrapartum fetal monitoring. She leads a pioneering program to create data-driven decision-support software for clinical use, aiming to improve outcomes through rigorous analysis of the world's largest complete birth cohort using routine labor data from 100,000 deliveries. In addition, she has been the principal investigator on the Wellcome LEAP In-Utero program, focusing on creating groundbreaking technology for continuous fetal monitoring. Georgieva joined the Nuffield Department of Obstetrics and Gynaecology and the Institute of Biomedical Engineering at Oxford for post-doctoral research in 2007 and secured a NIHR Career Development Fellowship in 2016 to establish her independent research group. Her work includes leading the Cross-disciplinary Machine Learning Cluster at Wolfson College and making significant strides in transforming clinical settings with novel cardiotocography systems that provide individualized risk assessments for fetal wellbeing. These developments aim to enhance the reliability of fetal monitoring during labor, thus potentially reducing complications and unnecessary interventions.
Oxford Labour Monitoring • Oxford, UK
Leading a research group focused on integrating clinical settings with novel data-driven cardiotocography systems/software for monitoring fetal wellbeing during labor.
Wolfson College, University of Oxford • Oxford, UK
Leading the Cross-disciplinary Machine Learning Cluster to collaborate with researchers across various disciplines.
Department of Politics and International Relations - Higher Level English requirement.