报告题目： Machine Learning and Internet of Things for Smart Health Systems
主讲人： 欧阳小敏，博士生，香港中文大学信息工程系
报告时间：2023年4月7日（星期五），14:30-16:00
报告地点：厦门大学海韵园行政楼A306
报告摘要：A key global challenge today is to deliver high-quality yet economically efficient healthcare solutions. The prominence of mobile devices and recent breakthroughs in machine learning have enabled an emerging class of new AI-powered mobile health systems that hold the promise of transforming today’s reactive healthcare practice to proactive, individualized care and well-being. This talk will introduce the design and deployment of an end-to-end Alzheimer’s Disease (AD) monitoring system that integrates multi-modal sensors and federated learning algorithms for detecting multidimensional digital biomarkers in natural living environments. This talk will also introduce our work on novel machine learning and sensing systems that address several challenges in smart health systems, including multi-modal activity recognition with limited labeled data, scalable federated learning, heterogenous multi-modal federated learning and ToF depth sensing.
报告人简介： Xiaomin Ouyang is currently a Ph.D. candidate at the Department of Information Engineering, The Chinese University of Hong Kong, supervised by Prof. Guoliang Xing and Prof. Jianwei Huang. Her research interests include Artificial Intelligence for Internet of Things and Networked/Embedded Systems, with a primary focus on developing novel machine learning and sensing systems for smart health applications. She obtained her Bachelor's degree from Information and Communication Engineering, Xiamen University in 2019.
邀请人：信息与通信工程系 付立群教授