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 IU Trident Indiana University

Pervasive Technology Institute

Innovation through Collaboration


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Center for Complex Networks and Systems Research (CNetS)

CNetS is hosted at the School of Informatics and Computing and brings together faculty from different units across campus working in the broad areas of complex networks and systems. The center activities include modeling and mining of complex information, technological and social networks, agent-based systems, computational social sciences, artificial life, computational epidemiology etc. The center is receiving funds by the Lilly Foundation through the PTI, NSF, NIH and a number of private foundations and corporations.

About CNetS

CNetS provides an internationally recognized center through which its members can develop theory, study data, create and implement algorithms, and apply computational techniques and simulations to complex networks and systems in nature, technology, and society. CNetS fosters and promotes existing and new academic collaborations of Computer Science and Informatics with various units on campus, including the departments of Psychology and Brain Sciences, Physics, Biology, Statistics, SLIS, Sociology, as well as other campus programs and centers such as the Cognitive Science Program and the Cyberinfrastructure for Network Science Center.  The center is also building strong relationships with other academic institutions that have similar research centers, nationally and internationally (e.g., the Gulbenkian Institute in Portugal, the Institute for Scientific Interchange Foundation in Italy, the Max Planck Institute for Human Development in Germany, the Complex Network Research Center at the University of Notre Dame, and others).

Center web page:

Mobility networks and the worldwide spread of epidemics

Networks which trace the activities and interactions of individuals,
transportation fluxes and population movements on the local and global
scale have been analyzed and found to exhibit large scale
heterogeneity, self-organization and other properties typical of
complex systems. This project aims at understanding the impact of the complexity of techno-social networks on the predictability limits and reliability offered by large-scale computational epidemic models. In order to do that,  Professor Vespignani’s team develops and analyzes realistic computational models for the large-scale spread of infectious diseases that integrate transportation networks with socio-demographic.

Bibliome informatics: literature mining

One of Luis Rocha's research threads has been to understand and utilize the Bibliome (the collection of online literature and database annotations) to infer bio-chemical and functional information about groups of genes and proteins. His research group has conducted large-scale analyses and validation of the Bibliome to successfully predict protein sequence and structure families, as well as to automatically identify protein-protein interactions in the literature.

Social Integration of Semantic Annotation Networks for Web Applications

This NSF funded project brings together complex networks and Web mining techniques to develop a new generation of search engines and collaborative Web applications such as Professor Menczer and collaborators will leverage existing annotations from users (such as the bookmarks they already maintain on their browsers) and elicit new ones through useful tools and games. The research will lead to a framework for building and maintaining socio-semantic networks of relationships between, and among, users, tags, and Web sites. For example, while users browse the Web, the framework will provide them with contextual social maps of related sites, people and topics. In the end, these networks will improve social Web applications such as search, recommendation, spam detection, and exploratory navigation interfaces.