Abstract

JWST ’s NIR Cam has transformed our understanding of galaxy structure in the early Universe through unprecedented spatial resolution and sensitivity. Deep wide and medium-band photometry enables precise rest-UV and optical SED constraints, revealing both opportunities and challenges for stellar population modeling.

I will present recent work on the galaxy stellar mass function and total stellar mass density evolution at z > 7, followed by spatially-resolved analysis of 200+ galaxies at z > 5. This reveals how internal structure affects integrated stellar mass estimates through ‘outshining’ effects. I will examine systematic uncertainties in high-redshift SED fitting—including IMF , SPS models, SFH parametrizations, and dust laws—and their impact on derived parameters.

Finally, I will discuss moving beyond traditional SED fitting using machine learning approaches, particularly simulation-based inference (SBI), for large-scale Bayesian inference from wide-area surveys. I will present ongoing work making SBI more accessible for fitting photometry and spectroscopy, enabling rapid constraints on stellar, nebular, and AGN properties in high-redshift galaxies.