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João Gama

Full Professor

Laboratory of Artificial Intelligence and Decision Support,
and Faculty of Economics,
University of Porto
Porto, Portugal

I'm a researcher at LIAAD - INESC TEC, the Laboratory of Artificial Intelligence and Decision Support of the University of Porto

I'm a Fellow of EurIA, the European Association for Artificial Intelligence (since 2020); and Fellow of IEEE (since 2021), 

ACM Distinguish Speaker


Scientific interests are:

  • Machine Learning
  • Learning from Data Streams
  • Ensembles of Classifiers
  • Constructive Induction
  • Probabilistic Reasoning

FCT Public key: J00878283U64

Publications at DBLP
Google Scholar 
ACM Digital Library 

Recent Books

Current Projects

Current Activities

PhD Students:

  • Thiago Andrade, MAPi, University of Porto
  • Mário Cordeiro, University of Porto
  • Shazia Tabassum, PRODEI, University of Porto
  • Sofia Fernandes, PDMA, University of Porto

Former Students:

  • Fabíola Fernandes, Universidade da Uberlândia, Brasil
  • Maria do Carmo Sousa, FEP, University of Porto
  • Marcia Oliveira, University of Porto
  • Elaine Faria, USP, Brasil
  • Luis Matias, PRODEI, University of Porto
  • Hadi Fanaee, MAPi, University of Porto
  • Carlos Ferreira, University of Porto
  • Raquel Sebastiao, PDMA, University of Porto
  • Petr Kosina, Masaryk University, Czech Republic
  • Rosane Maffei, ICMC, USP
  • Elena Ikonomovska, Josef Stefan Institute, Slovenia
  • Gladys Castillo, University of Aveiro
  • Eduardo Spinosa, University of Parana, Brasil
  • Pedro Pereira Rodrigues, University of Porto

Member of the Editorial Board: Machine Learning Journal, Data Mining and Knowledge Discovery, Intelligent Data Analysis and New Generation Computing, Progress in Artificial Intelligence, Knowledge and Information SystemsIEEE Transactions on Knowledge and Data Engineering

Member of APPIA (Associacão Portuguesa para a Inteligencia Artificial), IEEE, SIGAPP and SIGKDD


LIAAD-INESC Porto, Rua Dr. Roberto Frias, 378
4200-378 Porto, Portugal
Phone : (+351) 222 094 000
Fax : (+351) 222 094 050