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João Oliveira

Fotografia de João Gama Oliveira
Name: João Gama Oliveira Link to the personal page of João Gama Oliveira
Acronym: JGO
Status: Non active
Institutional E-mail: jgo@fe.up.pt
Voip: 3134


End Date: 31-08-2013
Category: Professor Auxiliar Convidado
Professional Group: Docente
Department: Department of Physics Engineering

Personal Presentation

I'm interested in a range of topics covered by the Statistical Physics of Complex Systems. In particular, my research focuses on understanding the structure, dynamics and complexity of systems (physical, biological, social, among others)* that can be represented as networks, i.e. whose fundamental feature is the connectedness between its constituent elements. Some examples of the phenomena under study are:

- Structural phase transitions in networks,
- The emergence and spread of epidemics in social systems or the Internet (computer virus),
- Sequential failures in electricity distribution systems,
- Coupling and synchronization of oscillators (describing, for example, seismic events, neuronal systems and the functioning of cells regulated by cardiac pacemakers),
- Searching for information in networks (eg locate information on the WWW)
- Traffic and flow of a physical quantity, data or information on networks,
- Molecular processes at the cellular level (cellular metabolism or interactions and protein folding).

This interdisciplinary field is often called Network Science and uses methods from graph theory (mathematics), statistical mechanics (physics), data mining (computer science), social structure (sociology), among others. Currently my approach to these phenomena is mainly theoretical (computational and analytical), although I have also used empirical approaches in the past.

ResearcherID : 

Google Scholar profile : http://scholar.google.com/citations?user=1Atij5cAAAAJ

* Examples include communication networks (Internet, WWW, telephone, email networks, road networks, airlines), biological networks (protein interaction networks, networks of metabolic reactions, gene-regulatory networks, neural networks, ecosystems), social (acquaintance networks, online social networks, networks of co-authorship of publications), technological networks (power or water supply networks).


Areas of interest

  1. Physical sciences
  2. Physical sciences > Physics > Statistical physics
  3. Physical sciences > Physics > Computational physics
  4. Physical sciences > Physics > Biophysics
  5. Physical sciences > Mathematics > Chaos theory
  6. Social sciences > Sociology > Societal behaviour
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