The 1st International Workshop on Ubiquitous Intelligence: AI-Driven Models for Smart Healthcare

Call for Papers

This workshop focuses on ubiquitous intelligence in smart healthcare, addressing the development of reliable and scalable AI-driven models and systems for real-world environments. Ubiquitous computing scenarios in smart healthcare typically face challenges such as domain shifts due to constantly changing users, devices, and contexts, as well as scarce labeled data, privacy and security constraints, and stringent real-time performance and energy budgets on the edge.

In this workshop, we welcome research submissions on time-series and sensor data modeling, including basic model and representation learning, self-supervised/semi-supervised learning, robust generalization across users/devices/contexts, passive transfer learning, and methods for few-shot/continuous personalization. This workshop also emphasizes edge and edge deployment, covering efficient model architecture, knowledge distillation, pruning, quantization/quantization-aware training, and energy-aware inference. Beyond detection and recognition, this workshop also focuses on contextaware decision-making and closed-loop interactions, such as personalized feedback, risk perception and prediction, and safety interventions in home and smart elderly care scenarios by integrating environmental intelligence or robotics. The workshop aims to connect algorithm, system, and application researchers in the UIC community to share datasets and evaluation protocols, implementation experiences, and best practices, thereby promoting the ubiquitous intelligent development of reliable, privacy-friendly, and human-centered smart healthcare.