Hong Chang

The paper proposes a scalable, helper-data-free open-set framework using an OpenGAN-based classifier to unify authentication for diverse and large populations of heterogeneous PUF-based IoT devices.

The paper proposes QT-PUF, a novel quantum tunneling leakage-based Physical Unclonable Function (PUF) designed for ultralow-power, implantable IoMT devices, achieving high reliability and minimal power consumption.

The paper introduces AnyMo, a unified multimodal framework that enables high-quality, scalable conditional human motion generation by leveraging a massive, cross-modal dataset and a masked modeling transformer.