Dr. Kai Wu has been recognized as a “Rising Star 2026” by Nanotechnology, an IOPscience journal. This recognition is associated with the group’s recent publication in Nanotechnology, titled “Data-driven and physics-informed estimation of magnetic nanoparticle properties via stochastic Langevin model”. In this work, the team addresses a key challenge in magnetic nanoparticle characterization: accurately extracting nanoparticle-specific parameters from AC magnetization measurements. The study presents a data-driven and physics-informed framework based on a stochastic Langevin model to simulate magnetization hysteresis and estimate magnetic particle properties under experimental conditions. This publication follows the group’s patent filing, “Identification of Magnetic Particle Parameters with Hardware Acceleration.”