1. CST5022 Quantitative principles in biological systems
Course coordinator: Po-Yi HO
Course credits: 3
Course time：Firdays 14:20-16:55
Course venue：E10-212, Yungu Campus
The course aims to provide a common "ruler" for researchers from diverse backgrounds to reason about biological systems. Topics are organized around broadly applicable themes like how biological systems deal with noise or optimize functions. Model systems span across scales from chemotaxis to proteins and microbiomes. Emphasis is on active learning through building models and analyzing data together.
2. CST4800 Frontiers in Computer Science and Technology
Course coordinator: Tailin WU
Course credits: 2
Course time：Thursdays 15:10-16:55
Course venue：E10-306, Yungu Campus
This course focuses on the current cutting-edge technologies in the field of computer science and technology, such as Artificial Intelligence, Deep Learning, AI for Science, etc. The lectures are divided into twelve topics, including Frontiers of Deep Learning, Generative Models, Large Models, Reinforcement Learning, Computer Vision and Autonomous Driving, AI + Life Sciences, AI + Scientific Computing, AI + Materials, etc. The content of each topic includes: the development history of theories/technologies, core concepts, underlying ideas and principle mechanisms, the latest research work and technology applications, technology development trends and/or future outlooks, and so on.