Research

City science and crime dynamics

Cities bring people together to interact; they can be seen as evolving systems that exhibit a global order built from local-level decisions. Though such local-level processes and decisions seem disordered, cities display striking regularities. In my research, I am interested in uncovering these regularities and building tools and models to understand urbanization better. In particular, I explore how crime exhibits regularities in its dynamics, structure, and growth.

Human dynamics and network inequality

Though our daily behavior looks sophisticated and unpredictable, recent research has shown that simple mechanisms can explain parts of our behavior dynamics (e.g., face-to-face interaction, human mobility). I am particularly interested in understanding how these mechanisms promote systemic biases into people's lives. For example, I explore how group interaction can drive social inequalities and investigate how our behavioral regularities (e.g., online, offline) make us predictable.

Computational intelligence

Swarm intelligence refers to the global order that emerges from simple social individuals interacting among themselves. In the past three decades, swarm intelligence has inspired many algorithmic models exhibiting distinct natural social behaviors, such as ant colonies and bird flocks. I investigate how to disentangle the complex behavior of computational swarms and make these algorithms more transparent.

Publications

Predictability states in human mobility (): Diogo Pacheco, Marcos Oliveira, Zexun Chen, Hugo Barbosa, Brooke Foucault-Welles, Gourab Ghoshal, and Ronaldo Menezes; arXiv (2022).
Group mixing drives inequality in face-to-face gatherings (): Marcos Oliveira, Fariba Karimi, Maria Zens, Johann Schaible, Mathieu Génois, and Markus Strohmaier; arXiv (2021).
More crime in cities? On the scaling laws of crime and the inadequacy of per capita rankings—a cross-country study (): Marcos Oliveira; Crime Science 10, 27 (2021).
Uncovering the social interaction network in swarm intelligence algorithms (): Marcos Oliveira, Diego Pinheiro, Mariana Macedo, Carmelo Bastos-Filho, and Ronaldo Menezes; Applied Network Science 5:24 (2020)
Spatio-temporal variations in the urban rhythm: the travelling waves of crime (): Marcos Oliveira, Eraldo Ribeiro, Carmelo Bastos-Filho, and Ronaldo Menezes; EPJ Data Science 7:29 (2018)
The scaling of crime concentration in cities (): Marcos Oliveira, Carmelo Bastos-Filho, and Ronaldo Menezes; PLOS ONE 12(8): e0183110 (2017)
Using Network Science to Assess Particle Swarm Optimizers (): Marcos Oliveira, Carmelo Bastos-Filho, and Ronaldo Menezes; Social Network Analysis and Mining 5:3 (2015)
Web Routineness and Limits of Predictability: Investigating Demographic and Behavioral Differences Using Web Tracking Data (): Juhi Kulshrestha, Marcos Oliveira, Orkut Karacalik, Denis Bonnay, and Claudia Wagner; Proceedings of the International AAAI Conference on Web and Social Media (ICWSM), 2021.
Characterizing the Social Interactions in the Artificial Bee Colony Algorithm (): Lydia Taw, Nishant Gurrapadi, Mariana Macedo, Marcos Oliveira, Diego Pinheiro, Carmelo Bastos-Filho, and Ronaldo Menezes; IEEE Congress on Evolutionary Computation (IEEE CEC). 2019.
The Influence of the Circadian and Ultradian Rhythms to Human Mobility: Empirical Evidences from Location-Based Check-Ins: Hugo Barbosa, Marcos Oliveira, Diogo Pacheco, Gourab Ghoshal, and Ronaldo Menezes; NERCCS 2018: First Northeast Regional Conference on Complex Systems, Binghamton, NY, USA. 2018.
Better Exploration–Exploitation Pace, Better Swarm: Examining the Social Interactions (): Marcos Oliveira, Diego Pinheiro, Mariana Macedo, Carmelo Bastos-Filho, and Ronaldo Menezes; 4th IEEE Latin American Conference on Computational Intelligence (LA-CCI), Arequipa, Peru. 2017.
Tippers and stiffers: An analysis of tipping behavior in taxi trips (): David Elliott, Marcello Tomasini, Marcos Oliveira, and Ronaldo Menezes; IEEE Ubiquitous Intelligence and Computing, San Francisco, California, USA. 2017.
Using Social Media to Assess Neighborhood Social Disorganization: a Case Study in the United Kingdom (): Diogo Pacheco, Marcos Oliveira, and Ronaldo Menezes; AI4BigData at the 30th International FLAIRS Conference, Marco Island, Florida, USA. 2017.
Communication Diversity in Particle Swarm Optimizers (): Marcos Oliveira, Diego Pinheiro, Bruno Andrade, Carmelo Bastos-Filho, and Ronaldo Menezes; ANTS 2016, Tenth International Conference on Swarm Intelligence, Brussels, Belgium. 2016.
From Criminal Spheres of Familiarity to Crime Networks (): Marcos Oliveira, Hugo Barbosa-Filho, Tobin Yehle, Sarah White, and Ronaldo Menezes; 6th Workshop on Complex Networks (COMPLENET), New York, USA. 2015.
Towards a Network-based Approach to Analyze Particle Swarm Optimizers (): Marcos Oliveira, Carmelo Bastos-Filho, and Ronaldo Menezes.; 2014 IEEE Symposium on Swarm Intelligence, Orlando, USA. 2014.
The Spatial Structure of Crime in Urban Environments (): Sarah White, Tobin Yehle, Hugo Serrano, Marcos Oliveira, and Ronaldo Menezes; 6th International Conference on Social Informatics (SocInfo 2014). First Workshop on Criminal Network Analysis and Mining, Barcelona, Spain. 2014.
Political Social Networks Reveal Strong Party Loyalty in Brazil and Weak Regionalism (): Marcos Oliveira, Carmelo Bastos-Filho, and Ronaldo Menezes; Sixth ASE International Conference on Social Computing, Stanford, USA. 2014.
Assessing Particle Swarm Optimizers Using Network Science Metrics (): Marcos Oliveira, Carmelo Bastos-Filho, and Ronaldo Menezes; 4th Workshop on Complex Networks (Complenet), Berlin, Germany. 2013.
Using Network Science to Define a Dynamic Communication Topology for Particle Swarm Optimizers (): Marcos Oliveira, Carmelo Bastos-Filho, and Ronaldo Menezes; 3rd Workshop on Complex Networks (Complenet), Melbourne, USA. 2012.
Optimizing a Routing Algorithm Based on Hopfield Neural Networks for Graphic Processing Units (): Carmelo Bastos-Filho, Marcos Oliveira, Denis Silva, Róbson Santana; IEEE Symposium on Foundations of Computational Intelligence (FOCI), Paris, France. 2011.
Uma Implementação em FPGA de Redes Neurais de Hopfield para Roteamento em Redes de Comunicação (): Marcos Oliveira and Carmelo Bastos-Filho; Anais do X Congresso Brasileiro de Inteligência Computacional, Fortaleza, Brazil. 2011
Car Setup Optimization Using Multi-Objective Swarm Algorithms (): Marcos Oliveira, Marcelo Lacerda, Érick Barbosa, Paulo Cordeiro, and Carmelo Bastos-Filho; Anais do X Congresso Brasileiro de Inteligência Computacional, Fortaleza, Brazil. 2011.
Impact of the Random Number generator quality on particle swarm optimization algorithm running on graphic processor units (): Carmelo Bastos-Filho, Marcos Oliveira, Débora Nascimento, and Alex Ramos; 10th International Conference on Hybrid Intelligent Systems, Atlanta, USA. 2010.
Sensing close-range proximity for studying face-to-face interaction (): Johann Schaible, Marcos Oliveira, Maria Zens, and Mathieu Génois; Handbook of Computational Social Science. Volume 1. Routledge, (2021)
Spatial concentration and temporal regularities in crime (): Marcos Oliveira and Ronaldo Menezes; To appear in "Understanding Crime through Science" (Springer Computational Social Sciences series). 2019.
Analysis of the Performance of the Fish School Search Algorithm Running in Graphic Processing Units (): Anthony Lins, Carmelo Bastos-Filho, Débora Nascimento, Marcos Oliveira, and Fernando Lima-Neto; Theory and New Applications of Swarm Intelligence. 1ed.: InTech. 2012.
Running Particle Swarm Optimization on Graphic Processing Units (): Carmelo Bastos-Filho, Marcos Oliveira, and Débora Nascimento; Search Algorithms and Applications. 1ed.: InTech. 2011.

Software

Here you can download code related to some research works:

network_swarm: A network-based approach to analyze particle swarm optimizers.
pso_gpu: Running Particle Swarm Optimization on graphic processing units
pso_dynamic_topology: A swarm with dynamic topology.
hnn_fpga: This is a VHDL model for Hopfield Neural Networks (HNN) for Routing in Communication Networks
spatial_reference: A helper to find out the correct spatial reference (EPSG) of a bunch of points using spatialreference.org.
partitions2graph: From partitions of a graph to a whole graph
graphml2metis: This converts a file from graphml to METIS format.
simulator: A simple tool to have experiments running in parallel.

Links

Some other connections to this page: GitHub, Gist, ResearchGate, and Google Scholar. Also, I am a proud last.fm user, I've been scrobbling for more than ten years! These are the albums I listened the most for the last three months:

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marcos oliveira

Research

City science and crime dynamics

Human dynamics and network inequality

Computational intelligence

Publications

Preprint

Journal

Conference

Book chapters

Software

Links