About Me

I am a cosmologist working at the interface of nonlinear structure formation, statistical inference, and galaxy surveys. My research develops forward-modeling and field-level Bayesian inference methods to extract maximal information from cosmic structure and use it to test growth, gravity, dark energy, and primordial physics.

My work includes the first 4-sigma evidence for a late-time suppression in the growth of large-scale structure, highlighted in Physical Review Letters and covered by Scientific American and New Scientist. I have also developed field-level Bayesian inference methods for galaxy surveys, a research direction that led to a second Physical Review Letters paper and the 2024 Buchalter Cosmology Prize.

I am currently a Kavli IPMU Fellow at the Kavli Institute for the Physics and Mathematics of the Universe, University of Tokyo. Before joining IPMU, I was a Leinweber Fellow at the University of Michigan and completed my PhD at the Max Planck Institute for Astrophysics and LMU Munich. My CV, research highlights, talks and travel, teaching, outreach, and contact information are available through the navigation tabs above.

Research Program

• Inference: field-level Bayesian inference, forward modeling, EFT-informed likelihoods, and simulation-based validation.
• Physics: growth of structure, gravity, dark energy, primordial physics, and consistency tests of ΛCDM.
• Surveys: galaxy clustering, weak lensing, CMB/LSS cross-correlations, and current or future surveys including PFS, DESI, Roman, Euclid, HSC, Rubin, and CMB-S4.