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Ziying (Olivia) Li
Olivia is a DPhil student funded by the Nuffield Department of Population Health, University of Oxford. Her research focuses on developing and validating trustworthy machine learning models and multi-agent systems for healthcare.
Across her previous work experience and research projects, she has developed machine learning models using diverse data modalities, from digital health-monitoring sensors to medical imaging. She has also worked on projects in evaluation and robustness, including surgical AI validation and benchmarking, and federated learning under data heterogeneity.
Before joining Oxford, Olivia completed her MPhil in Data Intensive Science at the University of Cambridge, MSc in Computational Neuroscience at Imperial College London, and BSc in Natural Sciences at University College London.
Ziying (Olivia) Li
Olivia is a DPhil student funded by the Nuffield Department of Population Health, University of Oxford. Her research focuses on developing and validating trustworthy machine learning models and multi-agent systems for healthcare.
Across her previous work experience and research projects, she has developed machine learning models using diverse data modalities, from digital health-monitoring sensors to medical imaging. She has also worked on projects in evaluation and robustness, including surgical AI validation and benchmarking, and federated learning under data heterogeneity.
Before joining Oxford, Olivia completed her MPhil in Data Intensive Science at the University of Cambridge, MSc in Computational Neuroscience at Imperial College London, and BSc in Natural Sciences at University College London.