Category Archives: Santo

Fortunato elected Fellow of the American Physical Society

Santo Fortunato has been elected Fellow of the American Physical Society (APS) for foundational contributions to the statistical physics of complex networks, and particularly to the study of community detection in networks and applications to social and scientific networks. The Fellowship is awarded annually to no more than one half of one percent of members of the APS for exceptional contributions to physics through research or publications, important applications of physics, leadership and physics education. Check the official press release of the school!

New paper in Nature Physics

In 2002 the paper Community structure in social and biological networks, by Michelle Girvan and Mark E. J. Newman, marked the beginning of network community detection, possibly the most popular topic in network science, which tackles the problem of automatically discovering communities — groups of nodes of the network that are strongly connected or that share similar features or roles.

Twenty years later, it’s time to see how the field is doing. In the Comment 20 years of network community detection, just published in Nature Physics, Santo Fortunato and Mark Newman present a brief overview of this fascinating topic and highlight future directions.

Fortunato elected Fellow of the Network Science Society

Santo Fortunato has been elected Fellow of the Network Science Society (NSS) for seminal work in network community structure leading to advances in multiresolution approaches and validation, and for contributions to disseminating network science. The Fellowship is awarded annually to members of the community for their exceptional lifelong individual contributions to any area of network science research and to the community of network scientists, both locally and globally. The award has been announced at NetSci 2022, the flagship event of the NSS. Fortunato is the first member of Luddy to receive this prestigious recognition. Check the official press release of the school!

Luddy AI Center

We’re moving and hiring!

We have two big announcements! First, CNetS (along with IUNI and OSoMe) is moving to the new Luddy Center for Artificial Intelligence. Second, we have a new tenure-track assistant professor position in Artificial Intelligence and Network Science. We welcome any candidates who study AI, complex systems, and network science (all broadly defined). Potential research areas include, but are not limited to, deep learning, graph neural networks, complex systems, complex networks, computational neuroscience, computational social science, social media analytics, agent-based models, and the impacts of AI and social media on society.  We especially welcome applications from members of underrepresented groups in computing. More info and application here!

New grant on AI and multilayer networks

The Army Research Office has awarded the grant Multilayer network embeddings and applications to real-world problems to CNetS faculty Santo Fortunato and Filippo Radicchi. The project lies at the interface between artificial intelligence and network science and aims at developing embeddings of multilayer networks in vector space. While graph embeddings have become very popular over the past decade, most of the research in this area focuses on the analysis of isolated graphs. However, networks in the real world do not exist in isolation, but they are coupled with other networks. For example in social media, the same person may interact with different individuals depending on the online platform. 

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CNetS @ NetSci 2020

CNetS students, postdocs, and faculty members will give 7 regular talks and present 13 posters at NetSci 2020, held online this year due to COVID-19. Regular talks will cover research on many topics including COVID-19, forecasting social contagion of anti-vax ideas, political bias in social media, coordinated manipulation online, the scientific development of nations, hierarchy in faculty hiring networks, and citation cartels in journals.

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New texbook from CNetS

The book A First Course in Network Science by CNetS faculty members Filippo Menczer and Santo Fortunato and CNetS PhD graduate Clayton A. Davis was recently published by Cambridge University Press. This textbook introduces the basics of network science for a wide range of job sectors from management to marketing, from biology to engineering, and from neuroscience to the social sciences. Extensive tutorials, datasets, and homework problems provide plenty of hands-on practice. The book has been endorsed as “Rigorous” (Alessandro Vespignani), “comprehensive… indispensable” (Olaf Sporns), “with remarkable clarity and insight” (Brian Uzzi), “accessible” (Albert-László Barabási), “amazing… extraordinary” (Alex Arenas), and “sophisticated yet introductory… an excellent introduction that is also eminently practical” (Stephen Borgatti). It was ranked by Amazon #1 among new releases in physics. More…

DREAM Challenge paper published in Nature Methods

DREAM Challenge
Structure of the Disease Module Identification DREAM Challenge

The outcome of the DREAM Challenge on Disease Module Identification in genetic networks has been reported in a paper published in Nature Methods. Over 400 participants from all around the world have contributed 75 different clustering algorithms to predict disease-relevant modules in diverse gene and protein networks. Participants could only use unsupervised clustering algorithms, which rely exclusively on the network structure and do not depend on additional biological information such as known disease genes. CNetS professor Santo Fortunato and former postdoc Lucas Jeub participated in the analysis of the results delivered by the algorithms.

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