I'm an assistant professor with a dual (50/50) appointment between the Institute for Theoretical Physics (ITP) and the Department of Information and Computing Sciences (ICS).
My main interdisciplinary research direction is in the application of techniques and ideas from physics and information theory to deep learning, as well as to neuro-inspired AI. For example, mathematical parallels between the structure of deep neural networks and renormalization group flow can be used to study the propagation of information in these models, and techniques from statistical field theory allow one to describe a general class of deep networks as a bona-fide quantum field theory (NN/QFT correspondence).
Additionally, as a theoretical physicist by training, I study aspects of holography, black holes, and quantum gravity more generally. I'm also interested in the application of operator algebras and quantum information theory to fundamental physics, such as the potential for modular theory to shed light on black hole interiors or entanglement entropy in QFT.
More information on my research interests can be found in my publications, which are indexed by Inspire and freely accessible on the arXiv, as well as on my research blog.
I am also passionate about making academia more inclusive, and am active in EDI: I am a member of the EDI committees of the ITP, the ICS, and the Department of Physics, and a member of the Faculty of Science EDI workgroups. As an openly non-binary transgender scientist, I strive to raise awareness of gender minorities in particular, as well as to create a safer academic culture for marginalized students/researchers of all backgrounds. My approach is intersectional, and I am especially interested in learning more about aspects of diversity that I have not experienced personally in order to better support those who have. If you wish to discuss any issues related to EDI, whether personal or systemic, please feel very welcome to approach me!