Courses

• Graph Neural Networks for Recommendation and Relation Estimation

  Semester：114-2

  Time and classroom：W234-M-b01[GF]

  Some complicated data involving relationships can be represented as a graph that consists of nodes and edges between nodes. Such graphs can serve as a fundamental tool for modeling social, technological, and biological systems. This course focuses on the computational, algorithmic, and modeling challenges specific to the analysis of massive graphs. By means of studying the underlying graph structure and its features, students are introduced to machine learning techniques and data mining tools that can help us to reveal insights into a variety of networks. We will focus on representation learning and Graph Neural Networks. Furthermore, we will cover algorithms for the World Wide Web, influence maximization, disease outbreak detection, and social network analysis.

• Information Security

  Semester：114-1

  Time and classroom：W234-M102[GF]

  This course introduces the fundamental concepts of information security including cryptography, network security, risk assessment, and security policies.

• Programming

  Semester：113-2

  Time and classroom：T567-MB210[GF]

  This course considers the basics of fundamental programming techniques using C++. Topics include the variables, expressions, control statements, functions, pointers, strings, arrays, and file operations.