Assistant Teaching Professor for AI and Physics in DAMTP and the Department of Physics, with his primary appointment in DAMTP. Working on the physics of learning and machine learning for fundamental physics. Head of Mathematical AI at the Cambridge–Infosys AI Lab.
Research: INSPIRE · Google Scholar · NASA ADS
Research team: Krippendorf Lab
Seminar: DAMTP DIS seminar
Publications
Parameter compression in the flux landscape
– Journal of High Energy Physics
(2026)
2026,
186
(doi: 10.1007/jhep07(2026)186)
Solving inverse problems of Type IIB flux vacua with conditional generative models
– Journal of High Energy Physics
(2026)
2026,
103
(doi: 10.1007/JHEP07(2026)103)
Beyond scaling curves: internal dynamics of neural networks through the NTK lens
– Machine Learning: Science and Technology
(2026)
7,
025005
(doi: 10.1088/2632-2153/ae4442)
Learning optimal summary statistics of galaxy catalogs with SBI
– Journal of Cosmology and Astroparticle Physics
(2025)
2025,
032
Spinodal Gravitational Waves
– Journal of High Energy Physics
(2025)
2025,
93
(doi: 10.1007/jhep11(2025)093)
Collective variables of neural networks: empirical time evolution and scaling laws
– Machine Learning: Science and Technology
(2025)
6,
035021
(doi: 10.1088/2632-2153/adee76)
Deep observations of the Type IIB flux landscape
– Journal of High Energy Physics
(2025)
2025,
271
(doi: 10.1007/jhep07(2025)271)
Towards a phenomenological understanding of neural networks: data
– Machine Learning Science and Technology
(2023)
4,
035040
(doi: 10.1088/2632-2153/acf099)
CYJAX: A package for Calabi-Yau metrics with JAX
– Machine Learning: Science and Technology
(2023)
4,
025031
(doi: 10.1088/2632-2153/acdc84)
A duality connecting neural network and cosmological dynamics
– Machine Learning: Science and Technology
(2022)
3,
035011
(doi: 10.1088/2632-2153/ac87e9)
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