Scope:

Extensive research has been developed aiming to developing computational tools for Smart Cities. Actually, researchers have focused their attention on using techniques of Data Mining and Machine Learning aiming more efficient and pleasant cities. For example, data acquired by imaging cameras distributed along a city square can be used to analyze its occupation with the use of dashboards, but also to estimate future occupations based on machine learning models in order to support better decision making as to, e.g., people and property security.

The main goal of the proposed “Data Mining and Machine Learning in Smart Cities”, is to bring together researchers involved in the related fields (Data Analytics, Pattern Recognition, Prediction and Simulation, Software Development, etc.), in order to set the major lines of development for the near future.

The proposed Workshop will consist of researchers representing various fields related to Data Mining, Artificial Intelligence, Machine Learning, Signal Processing, Computational Vision, Informatics, Statistics, Management, Architecture, Smart Cities, City Authorities, Policy Makers, etc., and endeavors to make a contribution to achieving better solutions for more efficient and pleasant cities, and attempts to establish a bridge between researchers from diverse fields.

 

List of topics of interest:

Topics of interest include (but are not limited to):

  • data pre-processing, classification and visualization;
  • big data and data analytics;
  • dashboard designing;
  • service designing;
  • feature extraction, selection and classification;
  • machine learning and deep learning;
  • pattern recognition and clustering;
  • signal processing and analysis;
  • computer vision and image processing and analysis;
  • traffic analysis, prediction and simulation;
  • route optimization and planning;
  • users and usage characterization;
  • surveillance systems;
  • computational decision making;
  • application of data mining tools in Smart Cities;
  • application of machine learning tools in Smart Cities;
  • software development for Smart Cities;

 

Organizing Committee:

  • João Manuel R. S. Tavares, Faculdade de Engenharia da Universidade do Porto, Portugal, This email address is being protected from spambots. You need JavaScript enabled to view it.
  • Marta Campos Ferreira, Faculdade de Engenharia da Universidade do Porto, Portugal, This email address is being protected from spambots. You need JavaScript enabled to view it.

 

Program Committee (Names and affiliations) (TBC)

  • Alexandre Xavier Falcão, Universidade de Campinas, Brazil
  • Arrate Muñoz Barrutia, University of Navarra, Spain
  • Constantine Kotropoulos, Aristotle University of Thessaloniki, Greece
  • Djemel Ziou, University of Sherbrooke, Canada
  • Fiorella Sgallari, University of Bologna, Italy
  • Francisco Perales, Balearic Islands University, Spain
  • Ghassan Hamarneh, Simon Fraser University, Canada
  • Hemerson Pistori, Dom Bosco Catholic University, Brazil
  • Huiyu Zhou ,Brunel University, UK
  • Igor Yanovsky, Jet Propulsion Laboratory, USA
  • Jason Corso, SUNY at Buffalo, USA
  • Javier Melenchón Maldonado, Open University of Catalonia, Spain
  • João Paulo Papa, Universidade de São Paulo, Brazil
  • Jorge M. G. Barbosa, Universidade do Porto, Portugal
  • Joaquim Gabriel Mendes, Universidade do Porto, Portugal
  • Jun Zhao, Shanghai Jiao Tong University, China
  • Luminita Vese, University of California at Los Angeles, USA
  • Manuel González Hidalgo, Balearic Islands University, Spain
  • Mario F. Montenegro Campos, Universidade Federal de Minas Gerais, Brazil
  • Metin N. Gurcan, Ohio State University, USA
  • Michael Liebling, University of California at Santa Barbara, USA
  • Norian Marranghello, Universidade Estadual de São Paulo, Brazil
  • Reneta P. Barneva, State University of New York, USA
  • Roberto Bellotti, University of Bari, Italy
  • Teresa Galvão ,Universidade do Porto, Portugal
  • Valentin Brimkov, State University of New York, USA
  • Victor Hugo C. de Albuquerque, Universidade de Fortaleza, Brazil
  • Zeyun Yu, University of Wisconsin at Milwaukee, USA