Gabriel Spadon

Gabriel Spadon

Ph.D. in Computer Science

Network Science & Artificial Intelligence

Short Biography

Introduction. I'm Gabriel Spadon de Souza, known by my peers as Gabriel Spadon. Education. I have a Ph.D. in Computer Science with honors from the University of Sao Paulo (USP) - Brazil, part of which was carried out at the Georgia Institute of Technology (GaTech) - USA. Additionally, I have a Master's and bachelor's in Computer Science and an Associate's Degree in Information Technology. Research Interests. I like Computer Science as a whole, but I have worked closely with Network Science and Artificial Intelligence. Breakthroughs. In the field of Network Science, I proposed a way to mix complex networks and machine learning to forecast human mobility between municipalities through censuses-collected urban indicators. Though in Artificial Intelligence, I created a new graph-based layer architecture and neural network model for time series forecasting. Research Goals. My current research goal is to find ways to bring deep learning to network science to enhance our understanding of the non-linearities behind complex networks and dynamic systems.

Professional & Higher Education

[2017-2021] Ph.D. in Computer Science with honors @ University of São Paulo - USP

  • Thesis: From Cities to Series - Complex Networks and Deep Learning for Improved Spatial and Temporal Analytics

  • Supervisor: José F. Rodrigues Jr., Ph.D.

[2015-2017] M.Sc. in Computer Science @ University of São Paulo - USP

  • Dissertation: Characterization of patterns and behaviors through the analytic processing of complex networks in urban systems

  • Supervisor: José F. Rodrigues Jr., Ph.D.

[2011-2015] B.Sc. in Computer Science @ São Paulo State University - UNESP

  • Monograph: Analysis and simulation of Apache Hadoop in virtual environments

  • Supervisor: Ronaldo C. M. Correia, Ph.D.

[2009-2010] Associate in Information Technology @ National Service of Commercial Learning - SENAC

Featured Publications

Journal articles

  • Spadon G., Hong S., Brandoli B., Matwin S., Rodrigues-Jr J. F., and Sun J. Pay attention to evolution: Time series forecasting with deep graph-evolution learning, 2021. IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE; and,

  • Spadon G., Carvalho A. C. P. L. F., Rodrigues-Jr J. F., and Alves L. G. A. Reconstructing commuters network using machine learning and urban indicators, 2019. Scientific Reports; and,

  • Spadon G., Machado B. B., Eler D. M., and Rodrigues-Jr J. F. Detecting multi-scale distance-based inconsistencies in cities through complex-networks (invited paper), 2019. Journal of Computational Science, Elsevier.

Book chapters

  • Spadon G., Gimenes G., and Rodrigues-Jr J. F. Topological street-network characterization through feature-vector and cluster analysis, 2018. 18th International Conference on Computational Science, Springer;

  • Spadon G., Machado B. B., Eler D. M., and Rodrigues-Jr J. F. A distance-based tool-set to track inconsistent urban structures through complex-networks (awarded paper), 2018. 18th International Conference on Computational Science, Springer; and,

  • Spadon G., Scabora L. C., Araujo M. V., Oliveira P. H., Machado B. B., Sousa E. P. M., Traina-Jr C., and Rodrigues-Jr J. F. Complex-network tools to understand the behavior of criminality in urban areas, 2018. 15th International Conference on Information Technology: New Generations, Springer.

Conference papers

  • Spadon G. and Rodrigues-Jr J. F. Computer-assisted city-touring for explorers, 2018. Workshop on Big Social Data and Urban Computing @ 44th International Conference on Very Large Data Bases, CEUR-WS;

  • Spadon G., Gimenes G., and Rodrigues-Jr J. F. Identifying urban inconsistencies via street networks, 2017. 17th International Conference on Computational Science @ Procedia Computer Science, Elsevier; and,

  • Spadon G., Scabora L. C., Oliveira P. H., Araujo M. V., Machado B. B., Sousa E. P. M., Traina-Jr C., and Rodrigues-Jr J. F. Behavioral characterization of criminality spread in cities, 2017. 17th International Conference on Computational Science @ Procedia Computer Science, Elsevier.

Grants & Awards

[05/2022] Grant & Fellowship

  • Title: Ocean Monitoring for Environmental Protection using Heterogeneous Spatio-Temporal Data using Neural and Complex Networks

  • Institutions: Ocean Frontier Institute (Canada), Dalhousie University (Canada), and ISBlue & IMT Atlantique (France)

[06/2021] Grant & Fellowship

  • Title: Vessel mobility patterns analysis and forecasting on irregular timing data using noise-robust neural networks

  • Institutions: Marine Environmental Research Infrastructure for Data Integration and Application Network (MERIDIAN)

[03/2019] Grant & Fellowship

  • Title: Advancing medical prognosis based on graph concepts and artificial neural networks

  • Identifier: FAPESP #2019/04461-9

[02/2019] Grant & Fellowship

  • Title: Analysis and improvement of urban systems using digital maps in the form of complex networks

  • Identifier: FAPESP #2017/08376-0

[06/2018] Award

  • Title: Best articles of the 18th International Conference on Computational Science, ICCS 2018 - Wuxi, China

[10/2017] Grant & Fellowship

  • Title: Pattern modeling and knowledge discovery in urban systems using complex networks and machine learning

  • Identifier: CNPq #167967/2017-7

[12/2015] Grant & Fellowship

  • Title: Characterization of patterns and behaviors through the analytical processing of real-world complex networks

  • Identifier: CAPES #9254601/M

[01/2015] Grant & Scholarship

  • Title: Emergency support for multi-user equipment at UNESP (laboratory specialist)

  • Identifier: PROPe #008/2015

[09/2014] Award

  • Title: Best articles of the Workshop on Scientific and Technological Initiation and Independent Projects (VII WICT-PI), ICMC - USP

[01/2014] Grant & Scholarship

  • Title: Support for multi-user and thematic projects (laboratory specialist)

  • Identifier: PROPe #008/2014

Follow me on RG, DBLP, ORCID, LinkedIn, Google Scholar, and also on GitHub.