ECE 498 LV  Network Science: Dynamics and Flow (Spring 2017)
Instructor: Lav Varshney (office hours, Thursday 12:302:00pm, 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 [openended topics, written report, and inclass conferencestyle presentations] (25%). Graduate students enrolled for 4 credits will complete an additional individual research project.
Homework
Exams
Final Project
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 



1/24 
3. Neuronal networks — human connectome and connectome of small organisms 



1/26 
4. Knowledge networks — citation, semantic, etc. 



1/31 
5. Mathematical representations, degrees, degree distributions, power laws 



2/2 
6. Software for network analysis [slides] 

2/7 
7. Review of differential equations, linear systems, and difference equations 



2/9 
8. (Scalar) dynamical systems 



2/14 
9. Dynamics on networks Guest Lecturer: Dr. Avhishek Chatterjee 


2/16 
10. Epidemics on networks Guest Lecturer: Dr. Avhishek Chatterjee 


2/21 
11. Synchronization 


2/23 
12. Information Cascades 


2/28 
13. Introduction to Network Flow 


3/2 
14. Computational Complexity and AllPairs Shortest Paths 


3/7 
15. Shortest Path via BFS and Dijkstra 


3/9  Exam  
3/14 
16. Flows and Cuts 


3/16 
17. Flows and Cuts II 


3/21  Spring Break  
3/23  Spring Break  
3/28 
18. Bottleneck Flow and Minimum Spanning Trees 



3/30 
19. Creativity and Engineering Applications [slides] 

4/4 
20. Multicommodity Flow 


4/6 
21. A* Algorithm for Path Planning Guest Lecturer: Dr. TingYi Wu 



4/11 
22. Node Centrality 


4/13 
23. Random Networks 


4/18 
24. Random Networks  ERGMs and Kronecker Graphs 


4/20 
25. Network Visualization 

4/25  Projects  Work Session  
4/27  Project Presentations  
5/2  Project Presentations 
Topics: