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Deep generative models are emerging as powerful tools for solving physics problems, enabling new approaches to inference, sampling, anomaly detection, and signal reconstruction. In the first part of the talk, I will discuss how generative models, designed with physical principles such as symmetry…

The stunning capabilities of modern AI systems give rise to many questions regarding how they work and how much more capable they can possibly get. One way to gain additional insight is via synthetic models of data with tunable complexity, which can capture the basic relevant structures of real data…

Axion-like particles can form clouds around rotating supermassive black holes through superradiant instability. Via axion-photon coupling, these clouds can imprint time-dependent oscillations on the observed electric vector position angle. I will present constraints on such clouds around M87* and…

The regularisation of entanglement entropy is integral to the possibility of it sourcing the Bekenstein-Hawking entropy. This regularisation ought to come from quantum gravity, which if covariant, can induce a regularisation scheme inapplicable directly on hypersurfaces, but instead suited to…

Modern physics is built upon three fundamental frameworks: quantum theory, general relativity, and information theory. In this talk, I will first introduce the field of relativistic quantum information, an operational framework that studies quantum information in relativistic settings by bringing…

Deformation quantization is a mathematical approach to understanding the quantization of classical mechanical systems. This talk will outline the procedure of deformation quantization and how it connects to the mathematical study of deformation theory. Time permitting, we will discuss some examples…

Quantum computers promise to simulate quantum systems and answer open questions across science from condensed matter and quantum chemistry to particle physics and quantum gravity. Two problems stand in the way: how to build them, and how to use them. Each brings hard optimisation, inference, and…

Optimal transport (OT) theory, first conceived to solve problems of moving dirt, has since evolved into a powerful mathematical framework with far-reaching applications across machine learning, probability and statistics, and theoretical physics. In particle physics, OT underpins many modern machine…

As a continuation of the canonical formulation of Loop Quantum Gravity, I will present an introduction to its covariant, path‑integral formulation in terms of spinfoams. Starting from the interpretation of spin networks as quantum states of geometry, I will explain how spinfoams arise as histories…

Axions are some of the best-motivated beyond the Standard Model particle candidates at present. These ultralight particles may account for the cosmological dark matter and explain other outstanding problems in nature, such as the strong-CP problem; they also are now known to emerge generically in…