معرفی
Sihan Yuan is a KIPAC Fellow in Astrophysics at Stanford University, developing simulation-based inference techniques to study dark matter and cosmic structure formation. His research combines trillion-particle simulations with Bayesian methods to constrain cosmological models.
As former simulation lead for the DESI collaboration, Yuan has contributed to cosmological constraints from baryon acoustic oscillations and galaxy clustering. His ABACUSHOD framework enables efficient multi-tracer halo occupation distribution modeling for large surveys.
Recent work includes developing k-nearest neighbor statistics for non-linear cosmological inference and generating synthetic light cones for weak lensing surveys. Yuan maintains active GitHub repositories for astronomical simulation tools and machine learning applications.
