5th ASDACS - Applied Statistics and Data Analysis using Computer Science


Applied Statistics and Data Analysis are areas that include a vast number of techniques developed in Computer Science such as numerical analysis, data visualization, machine learning and statistics.

A research, based on a certain theory regarding the topic under investigation, can propose some statements or hypothesis about the reasons of certain behaviour. The next step consists in testing some predictions with suitable experiments where several questions must be answered in order to obtain data. Depending on the outcomes of the experiment, the theory on which the hypotheses and predictions were based will be supported or not. By the nature of this line of scientific investigation the statistical methods assumes a major importance to determining the validity of empirical research. It is also important to quantify findings and present them with appropriate indicators of measurement. Several areas such as Medicine, Therapies, Biochemical Technology, Engineering and Economics relate Statistical Knowledge and Computer Science in order to analyse data obtained in the context of empirical research.

This workshop will provide researchers and practitioners a forum for exchanging ideas, experiences, problems understanding and visions for the future. The workshop will also provide a platform for researchers and developers to present results using the available tools and software packages for data analysis and to identify the problems in the theory and practice of empirical research recognizing future developments.


List of Topics

·         Applied Statistics and Data Analysis

·         Computer Science

·         Data collection strategies and methods

·         Selection and type of data

·         Strategies to enhance Quality of Data

·         Applicability for theory development and practice

·         Machine Learning and Automatic Scientific Discovery

·         Data Visualization

·         Decision based on Evidence

·         Empirical Research

·         Statistical and Data Analysis Software


Organizing Committee

·         Brígida Mónica Faria, School of Health/Polytechnic of Porto (ESS/P.Porto), Portugal

·         Joaquim Gonçalves, Polytechnic Institute of Cavado and Ave (IPCA), Portugal

·         João Mendes-Moreira, Faculty of Engineering, University of Porto, Portugal


Provisional Program Committee (to be confirmed)

·         Alberto Cardoso – Universidade de Coimbra

·         Andre PL Carvalho - Universidade de São Paulo

·         António Dourado – Universidade de Coimbra

·         Antonio Santos del Riego - Universidade da Coruña

·         Aurora Pozo - Universidade Federal de Minas Gerais

·         Bernardete Ribeiro – Universidade de Coimbra

·         Carlos Silla Jr. - Universidade Tecnológica Federal do Paraná

·         Carlos Ferreira – ISEP, P.Porto

·         Carlos Soares – Universidade do Porto

·         Celso Kaestner - Universidade Tecnológica Federal do Paraná

·         Daniel Castro Silva – Universidade do Porto

·         Gladys Castillo – Universidade de Aveiro e Choose Digital

·         João Alberto Fabro – Universidade Tecnológica Federal do Paraná

·         José Manuel Matos Moreira – Universidade de Aveiro

·         Julio Nievola - Pontifícia Universidade Católica do Paraná

·         Luís Filipe Meira Machado – Universidade do Minho

·         Luis Paulo Reis – Universidade do Porto

·         Myrian Delgado – Universidade Tecnológica Federal do Paraná 

·         Nuno Lau – Universidade de Aveiro

·         Pedro J. García Laencina – Centro Universitario de la Defensa de San Javier

·         Penousal Machado – Universidade de Coimbra·         

·         Theodoros Economou – University of Exeter

·         Tomás Horváth – Eötvös Loránd University in Budapest and Pavol Jozef Safárik University in Kosice

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