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Clara Grazian is an Associate Professor in the School of Mathematics and Statistics at the University of Sydney. She received her joint PhD in 2016 from the University of Paris-Dauphine, France, and Sapienza University of Rome, Italy. Her research focuses on Bayesian statistics and machine learning, particularly in developing statistical methodologies for environmental and biological sciences. Grazian has extensive experience addressing challenges related to uncertainty quantification, high-dimensional inference, and data-driven decision-making. She has worked at the Nuffield Department of Medicine and the Big Data Institute at the University of Oxford on a project investigating drug resistance mechanisms developed by tuberculosis. Her theoretical contributions include advancements in Bayesian mixture models and copula models, integration of deep learning with statistical modeling, and the development of robust frameworks for environmental risk assessments. Her interdisciplinary research spans areas such as statistics, AI, remote sensing, and genomics, collaborating with leading experts and institutions. Grazian actively supervises students and is aligned with the Faculty of Science's research strengths, particularly in data-driven decisions and precision digital health.
University of Sydney • Sydney, Australia
Teaching and research in statistical methodologies and data analysis.
University of New South Wales • Sydney, Australia
Conducted research and taught courses in statistics.
This entry applies to Faculty of Science PhD programs including Departments such as Life and Environmental Sciences, Physics, Chemistry, and Mathematics and Statistics.