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Rachel Wang is an Associate Professor in the School of Mathematics and Statistics at the University of Sydney. Her research focuses on the statistical theory and algorithms for joint inference in complex networks, contributing significantly to the understanding of underlying patterns within data. With a strong background in statistical network modeling, she has participated in various funded research projects including the Australian Research Council’s Discovery Early Career Researcher Award. Rachel's work aligns with the Faculty of Science's research strengths, specifically in the areas of understanding the universe, complex systems, and precision digital health. Her contributions to the field have been recognized through multiple grants, and she is actively involved in addressing challenges related to data-driven decision-making and national security.
University of Sydney • Sydney, NSW, Australia
Teaching and research in the Department of Statistics, focusing on statistical theory and its applications in various fields.
This entry applies to Faculty of Science PhD programs including Departments such as Life and Environmental Sciences, Physics, Chemistry, and Mathematics and Statistics.