Open to opportunities

Lynn Lin

@lynnlin

I build computational physics models and scalable scientific data-analysis pipelines.

I've developed computational physics models at UC San Diego, including an exactly solvable crystal lattice model that reduced structure-factor evaluations from quadratic to linear in phonon order for dark matter–nucleus scattering.

Previously at UC Santa Barbara, I co-developed and published a multi-scale optimal transport metric for collider events and built Bayesian inference pipelines across 2,500 simulated Milky Way-like halos, recovering halo mass within 1% of truth.

Experience

Work history, roles, and key accomplishments

Graduate Researcher

University of California, San Diego

Jan 2023 - Sep 2026 (3 years 8 months)

Developed an exactly solvable crystal lattice model for multiphonon dark matter–nucleus scattering, deriving a recursion relation that reduced structure factor evaluations from quadratic to linear in phonon order. Modeling qubit-phonon coupling in bulk acoustic resonators to quantify acoustic radiation as a qubit loss channel.