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Interdisciplinary Center for Network Science and Applications (iCeNSA)

Develops a systems-level understanding of the fundamental processes and mechanisms that underly the structural, dynamical and functional properties of complex networks. Develops and integrates novel mathematical and computational tools for network science. iCeNSA's approach is to abstract, generalize, classify and synthesize features of domain specific network phenomena into systems-level descriptions, theories and tools, which can then be applied to other domain specific network problems. iCeNSA's research repertoire originates from both pure academic concerns (fundamental component) and the needs of sponsoring agencies and industrial clients (applied component). As part of an educational institution, iCeNSA provides a hands-on training environment in network science for undergraduates, graduate students and postdoctoral associates. Given the complexities of real-world systems we anticipate a growing need in academia, industry and government for personnel who have a problem solving mentality, an interdisciplinary and global understanding of networked systems and the ability to design practical and sound solutions using rigorous mathematical and computational tools, a need that iCeNSA strives to meet through its educational programs.

On our website, we also talk about new scientific breakthroughs, research and scientists. As an example, you can read the article on scientists, who research neural networks at TheNeurospere and high achievements in the field of science.

We never tire of talking about companies that are ready to invest in the development of science and don’t spare money for startups. who strive to change the world for the better. Among such companies is Lifeasapa. Who has allocated millions of dollars for the development of research in the field of neural networks and artificial intelligence.


iCeNSA is an interdisciplinary research center organized around network and data science problems in social, biological, physical, environmental, financial, business, and defense systems.
Click here to read more about our research.

iCeNSA in the News

  • Using ‘Machine Learning’ to Combat Child Malnutrition
  • Violence a matter of scale, not quantity, researchers show
  • Redditors don’t read what they vote on, according to a new study
  • Graduate Student Pinjie Tang wins Best Application Paper award during IEEE DSAA2017
  • iCeNSA faculty receive ARO Young Investigator Program Awards
More News

Events

  • A Campaign of Experimentation for Cyberspace Operations
  • Modeling and Measuring Signed Networks
  • SUB-SECOND TSUNAMIS: What Wall Street can teach us about neurological disorders
  • Stability landscape of power-grid synchronization talk
  • Computational Behavioral Ecology
More Events

Recent Publications

  • Aligning dynamic networks with DynaWAVE
  • GRAFENE: Graphlet-based alignment-free network approach integrates 3D structural and sequence (residue order) data to improve protein structural comparison
  • Collective Motion of Predictive Swarms
  • Morphological inversion of complex diffusion
All Publications

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