Didier A. Vega-Oliveros

Researcher at CNetS - Indiana University Bloomington/USA

e-mail: davo at icmc dot usp dot br


Education    Projects    Publications    Links

About Me

Welcome to my professional Website!.

I am a Postdoctoral Research at the Center for Complex Networks and Systems Research (CNetS) in Indiana University, Bloomington – USA. I am also affiliated to the University of São Paulo - USP and a collaborative researcher at the National Institute for Space Research - INPE, both in Brazil.

My research activities are in complex networks, social networks analysis, data mining and information spreading models applied to big data. Currently, my fields of interests encompass machine learning based on graphs, modeling climate systems and disasters risk reduction and management. If you need further information or are interested in collaborations, please don't hesitate to contact me.

Education

Sep 2017 - Oct 2017

Research Visitor at Humboldt University of Berlin, Germany
Invited by Jürgens Kurths and supported by DFG-IGRK 1740/2 and FAPESP 2015/50122-0 joint project

Mar 2013 - May 2017

Ph.D. in Computer Science and Computational Mathematics
Advisors: Francisco A. Rodrigues and Luciano da Fontoura Costa
Univeristy of Sao Paulo - ICMC-USP - Brazil

2016

Research Visitor at National University of LaPlata, Argentina, in collaboration with Dr.Federico Vázquez and supported by Santander Scholarship award
2014

Visiting Scholar at Center for Complex Network Research (CCNR), Northeastern University, Massachusetts, U.S. In collaboration with Dr. Albert-László Barabási

Mar 2009 - Apr 2013

M.Sc. in Computer Science and Computational Mathematics
Advisor: Maria da Graça Campos Pimentel
Univeristy of Sao Paulo - ICMC-USP - Brazil

Sep 2003 - Oct 2008

B.Sc. in Computer Sciences and Engineering
Faculty of Engineering, National University of Colombia, Bogotá, D.C., Colombia

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Projects

  • Dynamical processes in complex network based on machine learning
    (Jul 2017 - Jun 2020)
  • In this project, we aim to develop methods to improve the tasks of machine learning based on graphs (networks), analyzing the impact the network structure has on the tasks. Also, through the use of multilayer networks, we will develop new methods for graph-based machine learning. The analyzes will be conducted considering the theory of complex networks and machine learning, using artificial and real databases, evaluating with literature methods and applying to real problems

  • Spatiotemporal data analytics based on complex networks
    (Feb 2019 - Feb 2020)
  • In this project, we aim to develop methods to analyze the patterns of activity and the evolution of spatiotemporal systems with dynamic networks. The project includes the design, development, and testing of new techniques for mining temporal and dynamic networks and the application of network analysis techniques to real-world problems.

  • Dynamic phenomena in complex networks: basics and applications
    (Sep 2017 - Nov 2021)
  • I am a research collaborator in this project, which seeks to continue the German-Brazilian cooperation initiative currently underway, aims to study the principles and foundations of self-organization in more general complex networks, where the topology is not simple and complexity is very elaborate. Aiming at applications in current situations of interest, it is intended to understand the role that structure heterogeneity, delays in multiple time and space scales, and stochasticity have on the network dynamics

  • Semi-supervised learning via complex networks
    (Oct 2018 - Sep 2020)
  • I am a research collaborator in this project, which investigates in depth all the steps involved in SSL, including the selection of initial labels, the selection of the network to be built and the method for propagating labels, and propose new approaches to improve this process. Challenges of the area will also be addressed such as contaminated or unbalanced labels, large databases and applications in text mining, climate data analysis and data augmentation for images

  • Sureale (Apr 2017 - Present)
  • I am researcher and developer in Sureale project, the startup that is an evolution in marketing allowing ultra-realistic and interactive experiences in virtual architecture environments. Interactivity with your product anytime, anywhere

  • BeeNet (Oct 2015 - Present)
  • I am collaborator and researcher in the BeeNet, a startup with state government financial support (FAPESP) that provides a new social network for the offering and searching for jobs that have a positive impact on people's lives

  • Agentto (Apr 2011 - Jan 2013)
  • I was the technical leader that coordinates the Semantic Framework team

  • TidiaAE (Mar 2009 - Oct 2009)
  • I was part of the developer team for a player in NCLua and SMIL to review a video conference session (chat, video and electronic whiteboard) for the DiGaE tool (Distributed Gathering Environment) of the TIDIA-Sakai

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