Welcome! I'm a research mathematician at the University of Sydney, dedicated to unraveling the intricacies of categorical algebra and representation theory. With a fervent belief in lifelong learning, I'm constantly driven by the pursuit of understanding and innovation.
My work primarily revolves around categorical representation theory, often referred to as 2-representation theory, strengthening its multifaceted applications. Bridging the realms of algebra, category theory, and topology, I delve into diverse areas such as modular representation theory, cryptography, and machine learning.
My research focuses on the dynamic intersections of categorical representation theory, where I explore applications across various fields. For instance, I'm currently investigating how principles of 2-representation theory can enhance cryptographic protocols and machine learning algorithms. Additionally, I'm delving into the properties of weighted KLRW algebras, examining their implications for modular representation theory and their potential impact on low-dimensional topology.
I'm passionate about fostering connections and collaborations. If you have ideas to share or questions you want to ask, don't hesitate to reach out at daniel.tubbenhauer@sydney.edu.au. Let's embark on this journey together!