糖心视频

Research

My group develops machine learning and statistical methods for observational cosmology. We investigate fundamental questions about dark matter, dark energy, the early Universe, and the growth of cosmic structure. One of our main goals is to build a unified, physically informed representation of the observable Universe. We combine multi-wavelength imaging and spectroscopy from different telescopes to infer redshifts, cosmic distances, and the physical properties of stars and galaxies directly from observations. By modelling instrumental effects and quantifying measurement uncertainties, we aim to recover information often lost in conventional analyses and use it to improve cosmological measurements and test our understanding of cosmic expansion and structure formation.

We welcome students and postdoctoral researchers who enjoy exploring new approaches and bring their own scientific questions and ideas. Visit the  for current projects and opportunities.