Dr. YEUNG Sai Kit 楊世傑博士

School of Arts and Social Sciences Teaching and Learning Writer/Artist/Scientist-in-residence Dr. YEUNG Sai Kit 楊世傑博士

楊世傑博士 Dr. YEUNG Sai Kit

駐校科學家 Scientist-in-Residence
期間:
2022年9月至12月
課程: 電腦及互動娛樂 (Computing and Interactive Entertainment)
The Scientist-in-Residence programme invited Dr. Sai-Kit YEUNG from the Division of Integrative Systems and Design (ISD) and the Department of Computer Science and Engineering (CSE) of the Hong Kong University of Science and Technology (HKUST). Dr. Yeung’s research expertise is in computer vision and computer graphics. His current research interests include 3D contents (scene and shape) reconstruction, understanding, modeling, and redesign, as well as computational design (using AI techniques for design and content generation), computational fabrication, visual understanding, and human-AI interaction. Beyond academia, Dr. Yeung was the founder of SKY Optimum Technology (SKYOPT), an interactive technology company in Singapore that provides a unified interactive visualization solution with the smart optimization technology adopted from Dr. Yeung's former research publications. The solution MagixHome VR (https://store.steampowered.com/app/537060/MagixHome_VR/) released in 2016 was used by Prime Minister's Office of the Singapore Government and featured well in Singapore media (https://www.straitstimes.com/singapore/singapore-government-adopting-indoor-3d-mapping-how-3d-mapping-works).

The Scientist-in-Residence programme had Dr. Yeung and his research group conducing a sequence of 12 workshops to enhance our Computing and Interactive Entertainment students in the area of computer vision in the context of interactive entertainment applications. Topics include
1) 3D Scanning and Geometry Processing;
2) Basic Deep Learning and its applications;
3) 2D and 3D Object Detection, Classification, and Segmentation;
4) AI algorithms for labeling and Content Generation;
5) Advanced topics and latest research works such as Neural Rendering using Generative adversarial network (GAN) and Neural Radiance Field (NeRF) were covered.