Professor: Boleslaw Szymanski — boleslaw.szymanski@gmail.com
Lectures: Mon & Thu 12:00 - 13:40, Sage 4510
Office Hours: Mon 14:00 - 14:45, Wed 11:00 - 11:45, webex by appointment
Teaching Assistant: Mauricio Gouvea Gruppi — mauricio.gruppi@gmail.com
Office Hours: Wednesday 15:00 = 16:00, webex at https://rensselaer.webex.com/meet/gouvem or by appointment
Textbook: Albert Laszlo Barabasi Network Science, Cambridge University Press, 2016
Description: This course offers an introduction to Network Science and a review of current research in this field. Classes will interchangeably present chapters from the textbook and the related current research. The emphasis will be on the mathematical background of network science: graphs and networks; random networks and various types of scale-free networks; and on network properties such as assortativity, mobility, and robustness; social networks and communities; and dynamics of processes on networks.
1--This is a web page for the class which contains the basic information about the course, lecture notes, assignments and their solutions, and comments. This page will also contain the corrections and general news about the course.
Course Content includes: (i) Mathematical background of network science: graphs and networks, (ii) Random networks and their properties, (iii) The scale-free property, small world networks and Barabasi-Albert model, (iv) Evolving networks, (v) Degree Correlation (vi) Network robustness, and (vii) Social networks and communities.
Overview and Introduction to Network Science (textbook chapter 1)
Overview Introduction to Network Science (pdf)(textbook chapter 1)
Research seminar: Detection of the source of spread in complex networks
Research seminar: Detection of the source of spread in complex networks (pdf)
Research seminar: Detection of the source of spread in complex networks Part II
Research seminar (pdf): Detection of the source of spread in complex networks Part II
Introduction to Network Science Part II (textbook chapter 1)
Introduction to Network Science Part II (pdf)(textbook chapter 1)
Graph Theory (textbook chapter 2) and Topics for Grad Presentations
Graph Theory (pdf) (textbook chapter 2) and Topics for Grad Presentations
Scale Free Networks (textbook chapter 3)
Scale Free Networks (pdf)(textbook chapter 3)
A guide for the graduate experiement plan write up due before lecture 15 on Oct. 17, 2022
Twitter Polarization, Dr. James Flamino
Adaptive Multiscale for Resolving Modularity Anomalies, Brendan Cross, CS
Noise-induced resilience restoration in ecology, Cheng Ma, Physics
CGC-Net: Cell Graph Convolutional Network for Grading Cancer Images_L, Vasundhara Acharya
Decay of collective memory and attention_L, Olivia Lundelius and Mara Schwartz
A guide for the experiement plan write up
The increasing dominance of teams_L, Linh Tran
Scientific prize network_L, Connor Wooding
Seminar: Response Prediction and Clustering on Social and Criminal Networks, Aamir Mandviwalla, CS
Controllability of complex networks, Yanna Ding (L),
Sequential Seeding, Yuxiao Li and Harry Sui (L),
Fast Algorithm for Community Detection, Megan Goulet (S)
Social network structure and composition in former NFL football players, Shawn George, (L)
Understanding individual human mobility patterns, Neha Deshpande (L),
Quantifying the future lethality of terror organizations, Richard Pawelkiewicz (S),
Quantifying reputation and success in art, Matt Zbikowski (L)
Brain Networks, James Oswald (L)
Epidemics on networks, John Jacob (S)
Beyond the Degree Distribution, Michael Leddy (S)
The product space conditions the development of nations, Astra Ford (L)
Entropy Measures of Human Communication Dynamics, Theodore Wu (S)
Testing Communities, Jack Bartley (S)
Social Networks through the Prism of Cognition, Luke Hamel (S)
Creation, Evolution, and Dissolution of Social Groups, Christos Kreatsoulas (S)
Presentation: Dynamics of Political Bias in Parler & Twitter, Mav Modi (L).