Leonardo N. Ferreira

Leonardo N. Ferreira
University of Oxford | OX · Big Data Institute

PhD in Computer Science
Senior Postdoc at University of Oxford

About

22
Publications
5,907
Reads
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216
Citations
Introduction
Leonardo is a computer scientist working on data science, machine learning, and network science. He holds a PhD from the University of São Paulo (USP), Brazil and has worked as a postdoctoral researcher at the National Institute for Space Research (INPE) from Brazil and as a visiting researcher at Northwestern University (USA), Humboldt University of Berlin, and the Potsdam Institute for Climate Impact Research.
Additional affiliations
March 2019 - February 2020
Humboldt-Universität zu Berlin
Position
  • Visiting researcher
March 2019 - February 2020
Potsdam Institute for Climate Impact Research
Position
  • Visiting researcher
October 2017 - May 2020
National Institute for Space Research, Brazil
Position
  • Postdoc
Education
February 2013 - March 2017
University of São Paulo
Field of study
  • Computer Science and Computational Mathematics
March 2010 - March 2012
University of São Paulo
Field of study
  • Computer Science and Computational Mathematics
July 2005 - July 2009
Universidade Federal de Lavras (UFLA)
Field of study
  • Computer Science

Publications

Publications (22)
Article
Full-text available
In this paper, we propose a technique for time series clustering using community detection in complex networks. Firstly, we present a method to transform a set of time series into a network using different distance functions, where each time series is represented by a vertex and the most similar ones are connected. Then, we apply community detectio...
Article
Full-text available
Protests diffusion is a cascade process that can spread over different regions of the planet. The way and the extension that this phenomenon can occur is still not properly understood. Here, we empirically investigate this question using protest data from GDELT and ICEWS, two of the most extensive and longest-running data sets freely available. We...
Article
Full-text available
The number of spatiotemporal data sets has increased rapidly in the last years, which demands robust and fast methods to extract information from this kind of data. Here, we propose a network-based model, called Chronnet, for spatiotemporal data analysis. The network construction process consists of dividing a geometric space into grid cells repres...
Preprint
Full-text available
Network science established itself as a prominent tool for modeling time series and complex systems. This modeling process consists of transforming a set or a single time series into a network. Nodes may represent complete time series, segments, or single values, while links define associations or similarities between the represented parts. R is on...
Article
Full-text available
Complex network theory provides an important tool for the analysis of complex systems such as the Earth’s climate. In this context, functional climate networks can be constructed using a spatiotemporal climate dataset and a suitable time series distance function. The resulting coarse-grained view on climate variability consists of representing dist...
Article
Full-text available
Uma característica inerente aos bancos de dados de acidentes rodoviários refere-se ao desequilíbrio existente entre o número de observações associadas às ocorrências dos acidentes com vítimas fatais e não fatais, em relação aos acidentes sem vítimas. Essa particularidade conduz à necessidade da aplicação de técnicas de balanceamento, que possibilit...
Preprint
Full-text available
The study and comprehension of complex systems are crucial intellectual and scientific challenges of the 21st century. In this scenario, network science has emerged as a mathematical tool to support the study of such systems. Examples include environmental processes such as wildfires, which are known for their considerable impact on human life. How...
Conference Paper
Full-text available
Chat groups are well-known for their capacity to promote viral political and marketing campaigns, spread fake news, and create rallies by hundreds of thousands on the streets. With the increasing public awareness regarding privacy and surveillance, many platforms have started to deploy end-to-end encrypted protocols. In this context, the group’s co...
Conference Paper
Full-text available
The study and comprehension of complex systems are crucial intellectual and scientific challenges of the 21st century. In this scenario, network science has emerged as a mathematical tool to support the study of such systems. Examples include environmental processes such as the wildfires, which are known for their considerable impact on human life....
Preprint
Full-text available
The number of spatiotemporal data sets has increased rapidly in the last years, which demands robust and fast methods to extract information from this kind of data. Here, we propose a network-based model, called Chronnet, for spatiotemporal data analysis. The network construction process consists of dividing a geometric space into grid cells repres...
Article
Full-text available
Fire activity has a huge impact on human lives. Different models have been proposed to predict fire activity, which can be classified into global and regional ones. Global fire models focus on longer timescale simulations and can be very complex. Regional fire models concentrate on seasonal forecasting but usually require inputs that are not availa...
Conference Paper
Full-text available
Network theory has established itself as an appropriate tool for complex systems analysis and pattern recognition. In the context of spatiotemporal data analysis, correlation networks are used in the vast majority of works. However, the Pearson correlation coefficient captures only linear relationships and does not correctly capture recurrent event...
Preprint
Full-text available
In this paper, we divide the globe into a hexagonal grid and we extracted time series of daily fire counts from each cell to estimate and analyze worldwide fire season severity (FSS), here defined as the accumulated fire detections in a season. The central question here is evaluating the accuracy of time series forecasting methods to estimate short...
Preprint
Full-text available
Network theory has established itself as an appropriate tool for complex systems analysis and pattern recognition. In the context of spatiotemporal data analysis, correlation networks are used in the vast majority of works. However, the Pearson correlation coefficient captures only linear relationships and does not correctly capture recurrent event...
Article
Full-text available
Reduced motor control is one of the most frequent features associated with aging and disease. Nonlinear and fractal analyses have proved to be useful in investigating human physiological alterations with age and disease. Similar findings have not been established for any of the model organisms typically studied by biologists, though. If the physiol...
Conference Paper
Full-text available
Time series clustering is a research topic of practical importance in temporal data mining. The goal is to identify groups of similar time series in a data base. In this paper, we propose a technique for time series clustering via community detection in complex networks. First, we construct a network where every vertex represents a time series conn...
Conference Paper
Full-text available
Complex networks are a unified form of rep-resenting complex systems. Through this representation is possible to study dynamical systems and make time series analysis using network techniques. One common charac-teristic of many real world time series is the periodicity. Detecting these periods is interesting because it permits to forecast the serie...
Conference Paper
Full-text available
Wireless Sensor Networks (WSN) are a special kind of ad-hoc networks that is usually deployed in a monitoring field in order to detect some physical phenomenon. Due to the low dependability of individual nodes, small radio coverage and large areas to be monitored, the organization of nodes in small clusters is generally used. Moreover, a large numb...

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Cited By

Projects

Projects (2)
Project
To evaluate the benefits that network science can bring to spatiotemporal data mining.