Clean water and clean air are vital for public health. This project focuses on developing high-efficiency and environmentally sustainable filters for removing harmful air/water pollutants. The team has developed novel architectures and functionalities for the filters to achieve high permeance, high removal efficiency, and excellent reusability.
All members of the HKU community and the general public are welcome to join!
Speaker: Dr Chenshu Wu, Assistant Professor, Department of Computer Science, Faculty of Engineering, HKU
Moderator: Dr Chenxiong Qian, Assistant Professor, Department of Computer Science, Faculty of Engineering, HKU
Date: 21st September 2023 (Thursday)
Mode: Mixed (both face-to-face and online). Seats for on-site participants are limited. A confirmation email will be sent to participants who have successfully registered.
Can machines sense without cameras or sensors? Computer vision allows machines to “see,” but their perception capabilities based on cameras are fundamentally limited to a specific field of view and good lighting conditions – they cannot see through any occlusions or in the dark. In this talk, I will introduce Wireless AI Perception that opens a new sense for machine perception to decipher the physical world, even in absolute darkness and through walls and obstacles. To achieve this, Wireless AI leverages ambient wireless signals for sensing and turns any Wi-Fi devices from a pure communication medium into a ubiquitous all-in-one sensing platform. We will first introduce the concepts, principles, and grand challenges of Wi-Fi sensing, and then share our unique solution of Wireless AI, which has been commercialized and deployed as real-world products, such as motion sensing, sleep monitoring, fall detection, indoor tracking, just to name a few. We foresee that Wi-Fi Sensing will enter billions of devices and millions of homes, and today is just the beginning of this revolution.