Network Science & Artificial Intelligence
Gabriel Spadon
Ph.D. in Computer Science
Introduction. I'm Gabriel Spadon de Souza, known by my peers as Gabriel Spadon. Education. I have a Ph.D. and MSc. in Computer Science from the University of Sao Paulo - Brazil. Part of my Ph.D. was at the Georgia Institute of Technology - USA. After that, I joined Dalhousie University - Halifax, NS - Canada, for a Postdoctoral Fellow position at the Institute for Big Data Analytics, co-hosted by Oceanix at IMT Atlantique - Brest, Brittany - France. Background. Since starting my graduate studies, I have worked with Data Science and Engineering, Network Science, and Artificial Intelligence and published several research articles on knowledge discovery through complex networks and data mining. Research Interests. Currently, I'm interested in neural-inspired models, graph-based databases, deep learning models, and complex network dynamics applied to human behavior and ocean sciences.
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
Research Group: Databases and Images Group (GBDI)
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
Research Group: Databases and Images Group (GBDI)
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
Research Group: Applied Computing Research Laboratory (LaPesCA)
Supervisor: Ronaldo C. M. Correia, Ph.D.
[2009-2010] Associate in Information Technology @ Nat. Service of Commercial Learning - SENAC
Featured Publications
Journal articles
Spadon G., Ferreira M. D., Soares A., and Matwin S. — Unfolding AIS transmission behavior for vessel movement modeling on noisy data leveraging machine learning, 2022. IEEE Access, IEEE;
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.
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
[06/2021] Fellowship Award
Title: Ocean Monitoring for Environmental Protection Using Heterogeneous Spatio-Temporal Data Using Neural and Complex Networks
Research Team: Marine Environmental Research Infrastructure for Data Integration and Application Network (MERIDIAN)
Research Institutions: Dalhousie University (Canada) and ISBlue & IMT Atlantique (France)
Funding: Ocean Frontier Institute (Canada)
[03/2019] Fellowship Award
Title: Advancing medical prognosis based on graph concepts and artificial neural networks
Identifier: FAPESP #2019/04461-9
[02/2019] Fellowship Award
Title: Analysis and Improvement of urban systems using digital maps in the form of complex networks
Identifier: FAPESP #2017/08376-0
[06/2018] Research Award
Title: Best articles of the 18th International Conference on Computational Science, ICCS 2018 - Wuxi, China
[10/2017] Fellowship Award
Title: Pattern Modeling and knowledge discovery in urban systems using complex networks and machine learning
Identifier: CNPq #167967/2017-7
[12/2015] Fellowship Award
Title: Characterization of patterns and behaviors through the analytical processing of real-world complex networks
Identifier: CAPES #9254601/M
[01/2015] Fellowship Award
Title: Emergency support for multi-user equipment at UNESP (laboratory specialist)
Identifier: PROPe #008/2015
[09/2014] Research Award
Title: Best articles of the Workshop on Scientific and Technological Initiation and Independent Projects (VII WICT-PI), ICMC - USP
[01/2014] Scholarship Award
Title: Support for multi-user and thematic projects (laboratory specialist)
Identifier: PROPe #008/2014