Faculty of Engineering

This 3D platformer running game is about a girl falling into a dream which guides her into a world called Roll-topia. In the communication with the residents of the local villages, she learned that the villagers were frustrated with the invaders who destroyed their houses. As a result, she decided to kick up the invaders. She uses cheese to attract attention to the greedy mice on the way to protect herself. In the end, she surprisingly arrived to the beginning point, only to find out this world is in the shape of a hamster wheel.

This project uses knowledge graph database analysis for repurposing existing drugs for COVID-19 treatment. The knowledge graph used in this projected was populated with various kinds of bioinformatic data relevant to the COVID-19 disease, the SARS-CoV-2 virus that causes it, as well as several thousand drugs. This data was then analyzed using three prevalent knowledge graph link prediction techniques: motif-based analysis, PageRank analysis, and machine learning analysis. This was used to generate scores for each drug in the database, with a higher score indicating greater probability in treatment of COVID-19. These proposed drug rankings were then cross-referenced with data on ongoing and completed COVID-19 drug trials, and it was found that of the top 20% proposed rankings, 120 are already undergoing trials, indicating high prediction accuracy. Additionally, as the main users of the project are supposed to be medical experts with non-technical backgrounds, a clean and easy to use interface was also designed for this system. The user interface consists of a proposed drug rankings table, a visualization of the scores of the top 50 drug candidates in the form of a bar graph, and list of literature relevant to each proposed drug along with sentiment analysis of the author’s attitudes towards use of each drug towards COVID-19 treatment. These features enable medical experts to identify the most promising drug candidates so that they can quickly move to the drug trial stage.

This is a Big-Data project catering to the needs of researchers at The University of Hong Kong. This project’s implementation in the form of a web-based system that enables easy flow of data-retrieval, visualization, and analysis that would fuel research into the fields of COVID-19 spread and MTR passenger behavior.

This project is participating the Robomaster ICRA AI challenge which aims to create an automatic small car which can conduct automatic navigation, decision making, auto-aiming (for shooting other robots). During the competition, robots will automatically navigate in an 8m * 4m competition region with barriers, localize itself, find the enemy robot, aim at its armor, and shoot it!

“With the increasing popularity and computation power of mobile devices, AR (Augmented reality) is more accessible. Video games, especially mobile games, can utilize AR technology to provide an immersive user experience. However, currently, most of the Mobile AR game usually lacks interactions between users and virtual objects due to the limited size and control interface of the device, nor can provide synchronized multiplayer expensive.

This project is to develop an AR interactive mobile game prototype that includes hand gesture control and world map sharing. We expect this technology can be applied in the education realm in the future.”

With Covid-19 raging around the world in 2020, it not only sheds light on the critical role of airports to curb the spread of commutable diseases but also reveals the importance of fever checking measures at airports. Therefore, the project explores the possibility of utilising the smart patrol robot for fever checking at the gate area. The project incorporated a thermographic camera on the robot and proceeded with different stages of data collection, data processing, and face recognition. A web portal has also been developed for fever case management.