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Daniel Tubbenhauer is a research mathematician at the University of Sydney, working in the School of Mathematics and Statistics. Their research is centered on categorical representation theory, with a focus on 2-representation theory, which is a significant area of research within modern algebra. They delve into the abstract theoretical aspects that have applications in areas such as analytic representation theory, with interests extending into modular representation theory, low-dimensional topology, algebraic combinatorics, and quantum physics. Daniel's latest research also encompasses cryptography and machine learning, exploring how representation theory can inform neural networks and cryptographic algorithms. As an active participant in the academic community, they are committed to supervising students and promoting personal growth in research. They emphasize their dedication to these fields through their personal website, which provides insights into their ongoing projects and research achievements.
University of Sydney • Sydney, NSW
Conducting research in categorical representation theory and its applications.
This entry applies to Faculty of Science PhD programs including Departments such as Life and Environmental Sciences, Physics, Chemistry, and Mathematics and Statistics.