Introduction to Network Science

Student/Faculty's Expectations on Teaching and Learning

Instructor: John C.S. Lui

This is an introductory course on "Network Science", in particular, we will learn various algorithms, mathematical principles, and software platforms for large scale networks analysis. In here, the networks can be both physical or logical networks. Logical networks include online social networks (e.g., Facebook, WeChat, Twitters, ...etc), Internet, Skype P2P networks, geo-distributed data center networks (DCNs), or cities which have mass amount of Internet-of-Things (IoTs) devices. Phyiscal networks include power plant networks, biological networks,..etc. In this course, we cover fundamental principles and algorithms for such large scale network analysis. Furthermore, how one can use these basic analytical tools and algorithms to understand the structures and dynamic of such networks. Note that this course is especially important since companies like Tencent, Alibaba and Huawei are looking for engineers to carry out large scale network analysis on their services/networks.

Teaching Assistants


Course Grades:

Policy: Late homework or programming assignments will NOT be considered.

FINAL EXAMINATION : Date December XX, X:XX pm to Y:YY pm, 2018. ZZZ Room XXX !!!!!! Final Examination :

Please note that the final examination is NOT an open-book exam. You are allowed to bring in one piece of A4 paper (or 2-pages) of ``cheat sheet'' . Topics to be covered in the final exam are:

Tentative Outline for the Course:

Lecture Notes: (Password Protected)

Administrative matter

Introduction to Network Science
Introduction to Technological Networks
Introduction to Social Networks
Introduction to Networks of Information
Mathematics of Networks
Performance Measures and Metrics
Large-scale Structure of Networks
Fundamental Network Algorithms
Matrix Algorithms and Graph Partitioning
Random Networks
Random Networks with General Degree Distributions
Theory of Network Formation
Network Models of Small-world and Exponential Random Graphs (*****)
Percolation and Network Resilience (*****)
Epidemics on Networks (*****)
Dynamical Systems on Networks (*****)
Network Search (*****)
Introduction to Theory of Submodularity
Calculation of Group Closeness Centrality
Analyzing Competitive Influence Maximization Problems with Partial Information
Boosting Information Spread: An Algorithmic Approach

Homework (Password Protected) Submission: Please submit your homework in class
Homework 1 (Deadline: Sept, XX, 2018. 7:00 pm, in the lecture period) Solution to Homework 1

More to come ....

Project (Password Protected) Submission: Please submit your programming project by Dec XX, 2018.
Programming Project (Graph Data for 964 nodes and 3,000 undirected edges)

Reference books:
Reference papers:
Related software: