Research

Much of twentieth-century physics was shaped by a single challenge: combining quantum mechanics with special relativity — the physics of the very small with the physics of the very fast. Scattering amplitudes sit at the center of this story. They are the numbers that encode what happens when particles collide, and the most direct predictions of quantum field theory. Remarkably, textbook methods for computing them — Feynman diagrams — produce calculations of enormous complexity, yet the final answers are often astonishingly simple. The on-shell program takes this hint seriously, building amplitudes directly from physical principles — consistency, unitarity, symmetry — rather than from Lagrangians and gauge redundancies. Using these methods, my work derived aspects of the Standard Model, including the Higgs mechanism, in entirely new ways.

In decentralized finance, I study a new class of financial systems made possible by blockchain technology. These transparent, programmable markets allow us to rethink how traditional finance works from the ground up — how trades are executed, how prices are discovered, and how liquidity is allocated. My work spans auction design (including the order flow auctions underlying UniswapX), automated market makers, and execution quality. I am also interested in where machine learning can be applied across the DeFi stack — from optimising auction parameters to improving price prediction and routing.