Events
Past Event
WED@NICO SEMINAR: Raissa D'Souza, University of California, Davis "Complex Networks with Complex Nodes: Emergent Behaviors and Control"
Northwestern Institute on Complex Systems (NICO)
12:00 PM
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Lower Level, Chambers Hall
Details
Speaker:
Raissa D'Souza, Professor and Associate Dean for Research, College of Engineering, University of California, Davis
Title:
Complex Networks with Complex Nodes: Emergent Behaviors and Control
Abstract:
Real world networks -- from brain networks to social networks to critical infrastructure networks -- are composed of nodes with nonlinear behaviors coupled together via highly non-trivial network structures. Approaches from statistical physics reveal the fundamental implications that complex network structure has on network function and resilience. In contrast, approaches from dynamical systems and control theory reveal the impact that nonlinear nodal dynamics have on emergent behaviors when connected together in simple networks. This talk presents recent work bridging the fields. We show that the interaction between the nodal dynamics and network structure can give rise to novel emergent synchronization behaviors and extend the analysis of cluster synchronization to hypergraphs, capturing higher-order interactions in networks. With respect to cascading failures, we show that adding in oscillatory nodal dynamics to classic models of self-organized-criticality leads to an emergent timescale and the occurrence of self-amplifying dragon king failures that wipe out the system. Finally, we discuss the frontiers of control of complex networks with non-linear nodes, identifying the key challenges and opportunities for bridging control theory, dynamical systems and statistical physics.
Speaker Bio:
Raissa D'Souza uses the tools of statistical physics and applied mathematics to develop mathematical models capturing the interplay between the structure and function of networks, including dynamical processes unfolding on networks. Her focus is on the abrupt onset of large-scale connectivity in networks, network synchronization behaviors and models of cascading failure. The general principles derived provide insights into the behaviors of real-world networks such as infrastructure networks and social networks, and opportunities to identify small interventions to control the self-organizing, collective behaviors displayed in these systems. She collaborates broadly with faculty within the college and in physics, statistics, political science and the Primate Center.
Location:
In person: Chambers Hall, 600 Foster Street, Lower Level
Remote option: https://northwestern.zoom.us/j/92514761999
Passcode: NICO2023
About the Speaker Series:
Wednesdays@NICO is a vibrant weekly seminar series focusing broadly on the topics of complex systems and data science. It brings together attendees ranging from graduate students to senior faculty who span all of the schools across Northwestern, from applied math to sociology to biology and every discipline in-between. Please visit: https://bit.ly/WedatNICO for information on future speakers.
Time
Wednesday, October 4, 2023 at 12:00 PM - 1:00 PM
Location
Lower Level, Chambers Hall Map
Contact
Calendar
Northwestern Institute on Complex Systems (NICO)
NICO DECEMBER SEMINAR: Scott Feld, Purdue University "Finding Highly Connected Nodes in Networks: The Power of Common Friends"
Northwestern Institute on Complex Systems (NICO)
11:00 AM
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Lower Level, Chambers Hall
Details
Speaker:
Scott Feld, Professor of Sociology, Purdue University
Title:
Finding Highly Connected Nodes in Networks: The Power of Common Friends
Abstract:
This paper extends the Friendship Paradox – where friends have more friends than random people do, on average – to the more general phenomenon that mutual friends have more friends than friends do, on average. We show that we can find people who who are friends of multiple people in practical sized random samples in one regional Facebook network of 63,392 people with an average of 24 friends each, where people with two friends in a random sample have an average of 212 friends overall, with three friends have an average of 391 friends, etc. We further illustrate this general network phenomenon by taking random samples of citations from 79,034 journal articles. We find that a source cited by two articles in a random sample has an average of 461 citations, placing it in the top 0.01% in numbers of citations among all sources cited by these articles. We provide a general expression for the expected overall number of friends of a person found to have k friends in a random sample from a population with a given distribution of numbers of friends. We show that the effectiveness of using common friends among random samples for finding highly connected nodes is most pronounced when there are nodes with a great disproportion of the ties, as seems to be both typical and important for many types of social and other networks, such as where there are superspreaders of diseases, mega-influencers on the Internet, and highly connected central nodes in centralized neural networks. We discuss further implications, applications, and directions for further research.
Speaker Bio:
Scott Feld served as Assistant to Full Professor of Sociology at the State University of New York at Stony Brook from 1975-1991. He then served as Professor of Sociology at Louisiana State University from 1991 until 2004, and joined the faculty at Purdue University in 2004. He has published over sixty articles, including twelve published in the most prestigious journals in the fields of Sociology and Political Science. His ongoing research interests involve 1) causes and consequences of patterns in social networks, 2) processes of individual and collective decision making, and 3) applications of sociology, most recently including innovations in marriage and divorce laws (covenant marriage). He regularly teaches undergraduate and graduate courses on social networks, research methods, and statistics.
Time
Tuesday, December 3, 2024 at 11:00 AM - 12:00 PM
Location
Lower Level, Chambers Hall Map
Contact
Calendar
Northwestern Institute on Complex Systems (NICO)