香港中文大学

Artificial Intelligence (AI) is an emerging engineering discipline that focuses on the technological innovations in enabling computing systems to behave and discover new knowledge with human-like intelligence. It is a broad area that covers many specializations, such as machine learning, deep learning, knowledge representation/inference, large scale computing systems and distributed systems, human-computer interactions, natural language processing, big data analytics, etc. It has evolved in multiple disciplines, such as finance, medicine, manufacturing, robotics, multimedia, telecommunications, computational linguistics, etc., and there is now a huge demand of AI specialists in both local and global employment markets. On the other hand, there are critical challenges on how to innovate and design solid and rigorous solutions for AI, as well as how to properly address the ethical and societal issues with AI.

Our newly proposed programme is designed to meet today's tremendous need of well-trained talents in AI and related specializations. It aims to equip students with the capabilities of designing and implementing AI systems and technologies that can analyze, reason about, and infer knowledge from massive information, backed by rigorous foundations of mathematics, basic sciences, data structures, statistics, algorithms, distributed computing, etc. Such capabilities enable students to develop cutting-edge AI solutions that are of practical interest to academics, industry, and society.

The programme offers four optional specialised streams for students to choose according to their own interests:

• Biomedical Intelligence
• Intelligent Multimedia Processing
• Large-scale Artificial Intelligence - Theory and Systems
• Intelligent Manufacturing and Robotics

Note that the aim of the AIST programme is to admit “elite" secondary school students, and the admission scores are expected to be higher than the broad based admission scores of Engineering at CUHK. Because of this, the AIST programme emphasizes on fundamental mathematics, sciences, theories, and compliment these knowledge with practical systems skillsets.

Expected Learning Outcomes

Upon completion of their studies, students will be able to:

• apply knowledge of mathematics, science, and engineering appropriate to the AI degree discipline (K/S);
• design and conduct experiments, as well as to analyze and interpret massive data (K/S);
• design a system, component, or process to meet desired needs within realistic constraints, such as economic, environmental, social, political, ethical, health and safety, manufacturability and sustainability (K/S/V);
• identify, formulate and solve AI-related engineering problems (K/S);
• understand professional and ethical responsibility (K/V);
• communicate and work effectively in multi-disciplinary teams (S/V);
• understand the impact of AI solutions in a global and societal context, especially the importance of health, safety and environmental considerations to both workers and the general public (K/V);
• recognize the need for and the importance of life-long learning (V); and
• use the techniques, skills, and modern computing tools necessary for engineering practice appropriate to the AI and computing discipline (K/S).

Remarks:

K = Knowledge outcomes

S = Skills outcomes

V = Values and attitude outcomes