Teaching

• CS8659 at CityU HK: Research in Computer Science. (co-lecturer)


• Introductory course for Ph.D. students.


• My lecture entitled "Understanding and Building Reliable Deep Neural Networks".


• GE2340 at CityU HK: Artificial Intelligence: Past, Present, and Future. [click to display details]


• Bachelor course for general education (GE).


Assessment - quiz 20%; group project 30%; midterm exam 20%; final exam 30%.


Lecture content overview


1. Mathematical Fundations of AI


2. Linear Models


3. Deep Learning


4. Optimization in AI


5. AI Security, Privacy and Ethics


6. Reinforcement Learning


7. AI Applications


8. Large Language Models


9. Recent Advances in AI
• CS1102 at CityU HK: Introduction to Computer Studies. [click to display details]


• Bachelor course for non-CS students.


• Demo code


Assessment - quiz 20%; group project 20%; midterm exam 24%; final exam 36%.


Lecture content overview


1. Binary Number System


2. Boolean Logic, Conditionals and Loops


3. HTML, CSS and Javascript


4. Hardware and Computer System


5. Computer Network


6. Operating Systems


7. Safety, Privacy and Ethics


8. Artificial Intelligence


9. Digital Media
Scratch and Javascript are taught in the lab sessions.