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Recent
Papers:
"Cascading Failures in
Spatially-Embedded Random Networks",
A. Asztalos, S. Sreenivasan, B.K. Szymanski, and G. Korniss, PLoS One 9(1): e84563 (2014). "Restoration Ecology: Two-Sex Dynamics and Cost Minimization", F. Molnar Jr., C. Caragine, T. Caraco, and G. Korniss, PLoS One 8(10): e77332 (2013). "Threshold-limited spreading in social networks with multiple initiators", P. Singh, S. Sreenivasan, B.K. Szymanski, and G. Korniss, Scientific Reports 3, 2330 (2013). "Minimum Dominating Sets in Scale-Free Network Ensembles", F. Molnar Jr., S. Sreenivasan, B.K. Szymanski, and G. Korniss, Scientific Reports 3, 1736 (2013). "Extraordinary Sex Ratios: Cultural Effects on Ecological Consequences", F. Molnar Jr., T. Caraco, and G. Korniss, PLoS One 7(8): e43364 (2012). "Evolution of Opinions on Social Networks in the Presence of competing Committed Groups", J. Xie, J. Emenheiser, M. Kirby, S. Sreenivasan, B.K. Szymanski, G. Korniss, PLoS One 7(3): e33215 (2012). "Social consensus through the influence of committed minorities", J. Xie, S. Sreenivasan, G. Korniss, W. Zhang, C. Lim, and B. K. Szymanski, Physical Review E 84, 011130 (2011). News: Science News Focus, "The power of true believers", by Adrian Cho RPI News, "Minority Rules: Scientists Discover Tipping Point for the Spread of Ideas", by Gabrielle DeMarco Discovery News, "Minority Rules: Scientists Find the Tipping Point", by Emily Sohn Freakonomics, "Minority Rules: Why 10 Percent is All You Need", by Matthew Philips Communications of the ACM, "Researchers Find Tipping Point to Sway Public Opinion", by Paul Hyman |
Current graduate students: Ferenc Molnar, Pramesh
Singh, Panagiotis Karampourniotis
Current postdocs: Sameet Sreenivasan,
Noemi Derzsy
Current undergraduate students: David
Galehouse, Matthew Kirby
Former graduate students: David Hunt,
Qiming Lu, Hasan Guclu, Balazs Kozma
Former postdocs: Andrea Asztalos
Former undergraduate students: Jefffrey
Emenheiser, Adam Freese
Collaborators: Boleslaw Szymanski
(Rensselaer), Zoltan Toroczkai (Notre
Dame), Chjan Lim
(Rensselaer)
Related publications:
"Interplay between
Structural Randomness, Composite Disorder, and Electrical
Response: Resonances and Transient Delays in Complex Impedance
Networks",
R. Huang, G. Korniss, and S.K. Nayak, Physical
Review E 80, 045101 (Rapid
Communication) (2009).
"Synchronization
in Weighted Uncorrelated Complex Networks in a Noisy
Environment: Optimization and Connections with Transport
Efficiency'',
G. Korniss, .Physical Review E
75, 051121 (2007).
"Extreme
Fluctuations in Noisy Task-Completion Landscapes on Scale-Free
Networks",
H. Guclu, G. Korniss, Z. Toroczkai, Chaos 17,
026104 (2007).
"Diffusion Processes on
Small-World Networks with Distance-Dependent Random Links'',
B. Kozma, M.B. Hastings, and G. Korniss, Journal of Statistical Mechanics: Theory and
Experiment, P08014 (2007).
"Threshold-Controlled
Global
Cascading in Wireless Sensor Networks'',
Q. Lu, G. Korniss, and B.K. Szymanski, in Proceedings of the Third
International Conference of Networked Sensing Systems (INSS
2006) (Transducer Research Foundation, San Diego, 2006)
pp.164-171.
"Scaling in
Small-World Resistor Networks'',
G. Korniss, M.B. Hastings, K.E. Bassler, M.J. Berryman, B. Kozma,
and D. Abbott, Phyiscs Letters
A 350, 324
(2006).
"Synchronization
Landscapes in Small-World-Connected Computer Networks'',
H. Guclu, G. Korniss, M.A. Novotny, Z. Toroczkai, and Z Racz, Physical Review E 73,
066115 (2006).
"Diffusion
Processes on Power-Law Small-World Networks'',
B. Kozma, M.B. Hastings, and G. Korniss, Physical Review
Letters 95, 018701 (2005).
"Extreme Fluctuations in Small-World-Coupled Autonomous Systems
with Relaxational Dynamics",
H. Guclu and G. Korniss, Fluctuation and Noise Letters
5, L43 (2005).
"Extreme
Fluctuations in Small-Worlds with Relaxational Dynamics'',
H. Guclu and G. Korniss, Physycal Review E 69,
065104(R) (2004).
"Suppressing
Roughness of Virtual Times in Parallel Discrete-Event
Simulations'',
G. Korniss, M.A. Novotny, H. Guclu, Z. Toroczkai, and P.A.
Rikvold, Science299, 677 (2003).
News: Science
Perspective,
"Rough
Times Ahead", by Scott Kirkpatrick,
The New York Times,
New Scientist,
Technology
Research News
"Roughness
Scaling for Edwards-Wilkinson Relaxation in Small-World
Networks'',
B. Kozma, M.B. Hastings, and G. Korniss, Physical Review
Letters 92, 108701 (2004).
"Small-World
Synchronized Computing Networks for Scalable Parallel
Discrete-Event Simulations'',
H. Guclu, G. Korniss, Z. Toroczkai, and M.A. Novotny,
in Complex Networks, edited by E. Ben-Naim, H.
Frauenfelder, and Z. Toroczkai, Lecture Notes in Physics Vol. 650
(Springer-Verlag, Berlin, 2004) 255--275.
"Stochastic
Growth in a Small World'',
B. Kozma and G. Korniss, in Computer Simulation Studies in
Condensed Matter Physics XVI, edited by D.P. Landau,
S.P. Lewis, and H.-B. Schuttler, Springer Proceedings in Physics
Vol. 95 (Springer-Verlag, Berlin, 2004), pp. 29-33.
"From Massively
Parallel Algorithms and Fluctuating Time Horizons to
Non-equilibrium Surface Growth'',
G. Korniss, Z. Toroczkai, M.A. Novotny, and P.A. Rikvold, Phys.
Rev. Lett. 84, 1351 (2000).
Social
Dynamics, Opinion Spreading, and Influencing in
Social Networks The current state of knowledge about the interdependency between structure, dynamics, and behaviors of large infrastructure, communication, and social networks is only at the preliminary stage. In this project, we investigate real data projected out from empirical social networks, to develop methodologies and techniques for extracting relevant information and behavioral patterns from the underlying social network. With the availability and accessibility of vast amount of data in recent years, our project will not only gain fundamental knowledge, from a network science viewpoint, but also will create methodologies and techniques that could be applied to address strategic and urgent needs aligned with national priorities for network research. For example, fighting irregular warfare (IW) is a complex and ambiguous inherently social phenomenon: "insurgency and counterinsurgency operations focusing on the control or influence of populations, not on the control of an adversary's forces or territory" (IW, Joint Operating Concept, 2007). To help operations in such an environment, we will develop and employ individual-based models to investigate social influencing and associated strategies in social networks. Our methods and models for community detection, community stability, and social influencing will be applicable to data sets of different types and spanning all scales, including those collected by the military. Mainstream ideology does not freely spread into an "ideological vacuum" as standard models for social influencing assume, but instead, is severely inhibited by existing adversary or extremist opinion clusters, strengthened by the collective identity of the individuals forming these extremist clusters. Therefore we develop and employ models for social dynamics with multiple (potentially coexisting) opinions. Investigating social dynamics and diffusion of opinions on empirical social graphs on graphs with multiple co-existing opinion clusters/communities, we will develop both heuristic and rigorous algorithmic methods to find influential nodes and to disintegrate or control adversary clusters in ideological warfare. We will systematically investigate the "influential hypothesis" in military-relevant scenarios. Over the past few years, we and the other
network science-researchers have been shifting the focus
of network research from structure to dynamics (or
function) in real-life networks. To accelerate this
transition, in this research we study social dynamics on
large-scale empirical social networks from a fundamental
viewpoint. Our investigations will focus on the
emergence and stability of communities in social graphs
and the elimination of such communities by introducing
agents committed to stabilizing society or by exerting
external/media influence. This research has been supported in part by ONR, ARL NS-CTA, and ARO The views and conclusions contained in this material are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Office of Naval Research, Army Research Laboratory or the U.S. Government. |
Related publications:
"Threshold-limited
spreading in social networks with multiple initiators",
P. Singh, S. Sreenivasan, B.K. Szymanski, and G. Korniss, Scientific
Reports 3, 2330 (2013).
"Minimum
Dominating Sets in Scale-Free Network Ensembles",
F. Molnar Jr., S. Sreenivasan, B.K. Szymanski, and
G. Korniss, Scientific Reports 3, 1736 (2013).
"Evolution
of opinions on social networks in the presence of competing
committed groups'',
J. Xie, J. Emenheiser, M. Kirby, S. Sreenivasan, B.K. Szymanski,
G. Korniss, PLoS One 7(3): e33215 (2012).
"Competition-Driven
Network
Dynamics: Emergence of a scale-free Leadership Structure and
Collective Efficiency'',
M. Anghel, Z. Toroczkai, K.E. Bassler, and G. Korniss, Physical
Review
Letters 92, 058701 (2004).
News:
Technology
Research News
Spatial Ecologies under
Temporal Variation
Better understanding the processes that allow one species to invade the habitat of another will help answer fundamental questions in ecology. Just as importantly, understanding the processes of biological invasion to the point of prediction should enhance our capacity to respond effectively to invading species that impose economic problems on agriculture and threaten native biodiversity across North America. Spatially structured biotic interactions generate demographic variation at the level of individuals; this variation can govern ecological invasion and competitive coexistence. Temporal abiotic variation can directly modulate demographic rates, exerting further effects on competitors' dynamics. Theory for individual-based spatial processes has remained distinct from theory for population dynamics in temporally variable environments. In this project, we study the interplay between discrete, stochastic spatial interactions and temporally varying environmental forces, with a focus on competitive invasion. To advance understanding of the multi-scale ecological complexity predicted by the theory, and to identify novel predictions, we apply concepts of statistical physics. When a superior competitor's invades an inferior resident species in a constant environment, and introduction occurs only rarely, spatial competition will be driven by local dispersal and mortality, so that we can apply the physical theory for nucleation of spatial systems. Low introduction rates and small environments may permit only single-cluster invasion by the superior competitor. Increasing the introduction rate or system size allows multi-cluster invasive growth. In both regimes, the invasion dynamics exhibits strong spatial correlation and stochasticity. Consequently, standard deterministic approaches fail to predict the behavior of the invasion process. However, for multi-cluster invasion, the time to competitive exclusion is approximated accurately by Avrami's law, an analytical framework of nucleation theory. The Avrami result links individual-level propagation and mortality rates to community-level features of spatial invasion, a major research objective in ecology. We are developing an integrative theory of stochastic spatial growth; judicious parameter choice should let the theory address data on invasive fronts ranging from the within-habitat to the biogeographic scale. To study invasion in two-dimensional environments, we analyze stochastic "roughening" of advancing fronts; several results apply to a broad class of spatial-growth models. Analysis has yielded novel predictions; habitat size (length of the front) should affect both invasion velocity and the expected location of the maximal invasive incursion beyond the front's mean position. Most importantly, we are developing a new theory for spatial competition in a time-varying environment. If each species is alternately favored, single-cluster invasion may admit competitive coexistence via stochastic resonance, indicating a matching of the (stochastic) spatial-dynamic and (periodic) environmental time scales. The multi-cluster mode may exhibit different limit cycles and long-term coexistence through large-scale clustering of each species, depending on comparison of the population dynamics characteristic time scale and the period-length of environmental variation. This research develops new approaches to understanding stochastic, nonlinear effects in ecological systems and will lead to insights concerning the way individual-based ecological interactions may amplify or attenuate environmental variability. This research has been supported in part by NSF-DEB (QEIB) Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. |
Related publications:
"Extraordinary
Sex Ratios: Cultural Effects on Ecological Consequences'',
F. Molnar Jr., T. Caraco, and G. Korniss, PLoS One 7(8):
e43364 (2012).
"Interference
Competition and Invasion: Spatial Structure, Novel Weapons and
Resistance Zones'',
A. Allstadt, Thomas Caraco, F. Molnar Jr., G. Korniss, Journal
of Theoretical Biology 306, 46 (2012).