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Universidade de São Paulo (USP). Instituto de Ciências Matemáticas e de Computação (ICMC) (Institutional affiliation for the last research proposal) Birthplace: Brazil
Gabriel Spadon is a Ph.D. candidate at the University of Sao Paulo, Brazil. His research focuses on the analysis of real-world urban systems represented as graphs. In this domain, he has published on topics related to knowledge discovery by means of complex networks and data mining techniques. Spadon has worked on the understanding of phenomena related to traffic, and criminality; and, on issues related to the optimization of urban grids. Although still in his early career, he has published on several international high-quality conferences and journals. (Source: Lattes Curriculum)
Complex networks contribute toward computational research and analysis through their ability to design systems modeled by vertices and edges, and by the attributes of their elements. They provide means to describe urban structures through their street mesh, expressing predicates that refer to the flow and transportation in an urban zone. The analysis of such structures is potentialized wh…
Deep learning (DL) has proven to succeed in a wide range of domains, ranging from acoustics and images to natural language processing. However, applying deep learning to graph-like data is a non-trivial task because of the unique properties of graphs. Recently, a significant amount of research efforts have been devoted to this area, notably improving graph analyzing techniques. Employing …
| 1 / 1 | Ongoing scholarships in Brazil |
| 1 / 1 | Completed scholarships abroad |
| 2 / 2 | All Scholarships |
| Associated processes | |
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
| Publications | 4 |
| Citations | 1 |
| Cit./Article | 0.2 |
| Data from Web of Science | |
RODRIGUES-, JR., JOSE F.; GUTIERREZ, MARCO A.; SPADON, GABRIEL; BRANDOLI, BRUNO; AMER-YAHIA, SIHEM. LIG-Doctor: Efficient patient trajectory prediction using bidirectional minimal gated-recurrent networks. INFORMATION SCIENCES, v. 545, p. 813-827, FEB 4 2021. Web of Science Citations: 0. (18/17620-5, 16/17078-0, 17/08376-0)
SPADON, GABRIEL; DE CARVALHO, ANDRE C. P. L. F.; RODRIGUES-JR, JOSE F.; ALVES, LUIZ G. A.. Reconstructing commuters network using machine learning and urban indicators. SCIENTIFIC REPORTS, v. 9, AUG 13 2019. Web of Science Citations: 0. (16/17078-0, 17/08376-0, 19/04461-9, 13/07375-0, 16/16987-7, 16/18615-0, 14/25337-0)
SPADON, GABRIEL; BRANDOLI, BRUNO; ELER, DANILO M.; RODRIGUES-, JR., JOSE F.. Detecting multi-scale distance-based inconsistencies in cities through complex-networks. JOURNAL OF COMPUTATIONAL SCIENCE, v. 30, p. 209-222, JAN 2019. Web of Science Citations: 1. (16/02557-0, 17/08376-0, 16/17078-0)
BRANDOLI, BRUNO; SPADON, GABRIEL; ESAU, TRAVIS; HENNESSY, PATRICK; CARVALHO, ANDRE C. P. L.; AMER-YAHIA, SIHEM; RODRIGUES, JR., JOSE F.. DropLeaf: A precision farming smartphone tool for real-time quantification of pesticide application coverage. COMPUTERS AND ELECTRONICS IN AGRICULTURE, v. 180, JAN 2021. Web of Science Citations: 0. (19/04461-9, 17/08376-0, 13/07375-0, 18/17620-5)