ECE 498 LV - Network Science: Dynamics and Flow (Spring 2017)

Instructor: Lav Varshney (office hours, Thursday 12:30-2:00pm, 314 CSL and by appointment)

Lectures: Tuesday and Thursday, 11:00am, 4070 Electrical and Computer Engineering Building

Adjacency matrix of C. elegans connectome (Varshney, et al., 2011) Volume of taxi rides in Manhattan on average Tuesday at 4PM, March 2009, http://www.binaryspark.com/heytaxi Backbone of the flavor network (Ahn, Ahnert, et al., 2011)

By taking an engineering perspective on network science, we can address these problems; more traditional problems in communications, computing, and power; and more!

Catalog Description: Network science studies connections and flows among interacting objects, and the dynamic evolution of these structures. This course will cover the mathematics of networks, drawing on an emerging set of principles and techniques that originate in engineering theory, physics, biology, and the social sciences. The goal is to equip students with conceptual tools for understanding complex network systems. Examples taken primarily from neuronal, knowledge, and infrastructure networks.

Suggested Prerequisites: ECE 210, ECE 313, MATH 286, MATH 415, or their equivalents. Programming in matlab and/or python.

Textbook: M. E. J. Newman, Networks: An Introduction, Oxford University Press, 2010. Note that further readings and lecture notes will be provided through the course website.

Grading: Homework [including data/programming assignments] (35%), midterm exam (20%), final exam (20%), group project [open-ended topics, written report, and in-class conference-style presentations] (25%).  Graduate students enrolled for 4 credits will complete an additional individual research project.

Syllabus, Syllabus Attachment


Homework

Exams

Course Schedule

Date Topic Reading Assignment Learning Objectives Multimedia Supplements
1/17

1. Introduction to networks and their mathematical abstraction

[slides

1/19

2. Infrastructure networks — electricity, water, communications

[slides] [handwritten notes]

  • Chapter 2 of Newman
  • Chapter 4 of Cannon (1967)
1/24

3. Neuronal networks — human connectome and connectome of small organisms

[slides[handwritten notes]

1/26

4. Knowledge networks — citation, semantic, etc.

[slides] [handwritten notes]

  • Chapter 4 of Newman
1/31

5. Mathematical representations, degrees, degree distributions, power laws

[slides[handwritten notes]

  • Chapter 6 and 8.3-8.4 of Newman
2/2

6. Software for network analysis

[slides]

   
2/7

7. Review of differential equations, linear systems, and difference equations

[handwritten notes]

  • Notes from prior courses
2/9

8. (Scalar) dynamical systems

[slides] [handwritten notes]

  • Chapter 18.1 of Newman
2/14

9. Dynamics on networks

Guest Lecturer: Dr. Avhishek Chatterjee

  • Chapter 18.2 and 18.3 of Newman
 
2/16

10. Epidemics on networks

Guest Lecturer: Dr. Avhishek Chatterjee

  • Chapter 17 of Newman
2/21

11. Synchronization

[slides] [handwritten notes]

2/23

12. Information Cascades

[slides] [handwritten notes]

 
2/28

13. Introduction to Network Flow

[slides] [handwritten notes]

 
3/2

14. Computational Complexity and All-Pairs Shortest Paths

[slides] [handwritten notes]

 
3/7

15. Shortest Path via BFS and Dijkstra

[slides] [handwritten notes]

  • Chapter 10.3 and 10.4 of Newman
 
3/9 Exam      
3/14

16. Flows and Cuts

[slides] [handwritten notes]

  • Chapter 6.12 of Newman
   
3/16

17. Flows and Cuts II

[handwritten notes]

  • Chapter 10.5 of Newman
   
3/21 Spring Break      
3/23 Spring Break      
3/28

18. Bottleneck Flow and Minimum Spanning Trees

[slides] [handwritten notes]

 
3/30

19. Creativity and Engineering Applications

[slides]

     
4/4 20. Multicommodity Flow      
4/6

21. A* Algorithm for Path Planning

Guest Lecturer: Dr. Ting-Yi Wu

     
4/11        
4/13        
4/18        
4/20        
4/25 Project Presentations      
4/27 Project Presentations      
5/2 Project Presentations      

Topics: