Kleber A. Oliveira

Kleber A. Oliveira

Assistant Lecturer

Munster Technological University

Biography

I am starting in Autumn 2024 as an Assistant Lecturer at Munster Technological University, Ireland.
Previously, I was a researcher at the CENTAI Institute in Turin, Italy.
I completed a PhD in Applied Mathematics supervised by Prof. James Gleeson, at the Mathematics Applications Consortium for Science and Industry (MACSI) of the University of Limerick, Ireland.

My research interests are in the space of online social networks, information diffusion and nonlinear dynamics. My CV can be retrieved by writing slash media slash cv dot pdf at the end of the current URL.

Interests
  • Network Science
  • Computational Social Science
  • Nonlinear Dynamics
  • Data Science
Education
  • PhD in Applied Mathematics, 2022

    University of Limerick, Ireland

  • MSc in Computer Science, 2018

    State University of Campinas, Brazil

  • BSc in Computational and Applied Mathematics, 2015

    State University of Campinas, Brazil

Recent & Upcoming Talks

Diffusion Approximation of a Network Model of Meme Popularity - NS22
Oral presentation given at the SIAM Workshop on Network Science 2022, which was held online. This work has a pre-print available.
Diffusion Approximation of a Network Model of Meme Popularity - NS22
Hierarchical Route to Emergence of Leader Nodes - CCS2020
Oral presentation given at the Conference on Complex Systems 2020, which was held online. This work has been published.
Hierarchical Route to Emergence of Leader Nodes - CCS2020

Recent Publications

(2024). Echo chamber formation sharpened by priority users. iScience.

DOI

(2023). Diffusion approximation of a network model of meme popularity. Phys. Rev. Research.

DOI

(2023). Modelling meme popularity with networks. University of Limerick Research Repository.

DOI

(2022). An actor-based approach to understanding radical right viral tweets in the UK. J. Polic. Intell. Count. Terror..

DOI

(2021). Hierarchical route to the emergence of leader nodes in real-world networks. Phys. Rev. Research.

DOI