Seokhyun Chung
Assistant Professor
About
My research focuses on the Internet of Things (IoT)-enabled systems, where multiple entities/units (e.g., vehicles, wearable devices, etc.) collect data and collaborate to establish enhanced smart analytics based on their connectivity. I enjoy exploring data-driven methods such as federated learning, multi-task learning, and Bayesian probabilistic modeling, to tackle key challenges arising in data analytics for connected systems, including statistical/systems heterogeneity, fast personalization, and inscalability. As such, I aim to advance smart & connected healthcare and manufacturing systems and their reliability.