Daniel Tubbenhauer

Dr. Daniel Tubbenhauer is an ARC Future Fellow at the University of Sydney's School of Mathematics and Statistics, specializing in categorical representation theory, 2-representation theory, and their applications to topology, cryptography, and machine learning. His research bridges algebra, category theory, and low-dimensional topology, with a focus on modular representation theory and diagrammatic algebra.

Education: PhD in Mathematics (2013), supported by extensive postdoctoral research globally.

Research Interests: He explores categorical structures in representation theory, including categorification of quantum groups, link homologies, and applications in cryptography. His work emphasizes diagrammatic methods and computational approaches to algebraic problems.

Publications: Over 30 peer-reviewed articles, including foundational work on web categories, Soergel bimodules, and applications of representation theory to machine learning. Recent projects analyze growth rates in tensor powers and fractal behavior in algebraic structures.

Awards: Australian Research Council Future Fellowship (2023), supporting his research on categorical representation theory.

Teaching & Supervision: Taught courses on quantum topology, category theory, and representation theory. Current student: Daniel Collison (PhD). Advises on projects linking representation theory to AI and cryptography.

Labs/Teams: Collaborates with global networks in algebraic topology and categorification, including projects at the Sydney Mathematical Research Institute. Maintains an active YouTube channel (VisualMath) for outreach.