報告題目: Creating a Better Future: Harnessing AI for Social and EnvironmentalResponsibility

報告人：Sam Kwong （鄺得互），香港嶺南大學副校長，講座教授。IEEE Fellow，香港工程科學院院士，美國國家發(fā)明家科學院院士

報告時間：2024年6月7日下午4點

報告地點：信息南樓A421

講者簡介：Professor KWONG Sam Tak Wu is the Chair Professor of Computational Intelligence, and concurrently as Associate Vice-President (Strategic Research) of Lingnan University. Professor Kwong is a distinguished scholar in evolutionary computation, artificial intelligence (AI solutions, and image/video processing, with a strong record of scientific innovations and real world impacts. Professor Kwong was listed as one of the top 2% of the world's most cite scientists, according to the Stanford University report. He was listed as one of the most highly cited scientists by Clarivate in 2022 and 2023. He has also been actively engaged in knowledge transfer between academia and industry. He was elevated to IEEE Fellow in 2014 for his contributions to optimization techniques in cybernetics and video coding. He was the President of the IEEE Systems, Man, and Cybernetics Society (SMCS) in 2021-2023. Professor Kwong has prolific publication record with over 350 journal articles, and 160 conference papers with an h-index of 82 based on Google Scholar. He is currently the associate editor of many leading IEEE transaction journals. He is a fellow of the US National Academy of Innovators. and the Hong Kong Academy of Engineering and Sciences.

報告摘要：In this talk, the speaker will delve into various questions related to AI applications and the positive impact on society and the environment. The talk will draw on examples of specific AI applications that are already making a difference. For instance, the underwater instance segmentation, which is the process of detecting and segmenting objects in underwater image. This technology has the potential to improve underwater exploration, marine conservation, and disaster response efforts. Another example is image reconstruction based on compressive sensing. This technique allows for the reconstruction of high-quality images from a limited amount of data which can be particularly useful in applications such as medical imaging or remote sensing. The third topic is the low night image enhancement, which is a technology that enhances images taken in low-light conditions. This can improve the accuracy and effectiveness of applications such surveillance, transportation safety, and security. By exploring these and other examples of AI applications, the talk aims to demonstrate the potential of Al to make a positive impact on society and the environment, and to inspire further imnovation.