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: Professor Raymond Ng, Canada Research Chair on Data Science and Analytics, Founding Director of the UBC Data Science Institute and Elected Fellow of the Royal Society of Canada
Moderator: Professor Benjamin Kao, Professor, Department of Computer Science, Associate Head, Innovation Academy, The University of Hong Kong
Date: 5th April 2024 (Friday)
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.
Unstructured documents often come with embedded structured data. Representing valuable and structured information as tables is popular in health, financial, and many domains. However, manual extraction of structured information from documents typically costs tremendous time and labor, motivating the need for a system for automating the process. After such tables have been extracted, the data can be used for a wide variety of tasks such as question answering and various “down-stream” analytics tasks. In this talk, we will discuss how to leverage ground breaking pre-trained language models (e.g., BERT, ChatGPT) to develop tools for automated table extraction from various types of documents. We will present different applications from cancer registry reporting, cancer care, and psychiatry hospitalization prediction.