Artificial Intelligence

Artificial intelligence, as a technological field, has enabled the creation of effective products and solutions (e.g., mobile robotics, search engines, product recommendation systems) through recent advancements in knowledge representation, machine learning, and reasoning with imperfect information. As a research discipline, AI is vast, covering key areas such as machine learning, knowledge representation, planning, reasoning, constraint satisfaction, natural language processing, and multi-agent systems. Research contributions in AI can be theoretical, technical, or applied. Applied research also drives the advancement of AI techniques in emerging fields such as security, sustainability, healthcare, human well-being, transportation, commerce, and Industry 4.0.

Faculty:

Alceu de Souza Britto Jr.

  • PhD, Pontifical Catholic University of Paraná, 2001.
  • CNPq Research Productivity Researcher.
  • Image Processing, Pattern Recognition.

 

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Andre Gustavo Hochuli

  • PhD, Pontifical Catholic University of Paraná, 2019.
  • Computer Vision, Pattern Recognition, Machine Learning

  

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Carlos Nascimento Silla Junior

  • PhD, University of Kent, Inglaterra, 2011.
  • CNPq Research Productivity Researcher.
  • Member of ACM, IEEE, ISMIR, SBC.
  • Data Mining, Computational Intelligence, Music Information Retrieval, Computer Music Technology.

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Edson Emílio Scalabrin

  • PhD, Université de Technologie de Compiègne, France, 1996.
  • Process Mining, Distributed Artificial Intelligence, Trust & Reputation, Blockchain, Biological Data Analysis, and Biological Data Compression.
  • Member of IEEE.

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Emerson Cabrera Paraiso - PPGIa Head of the Department

  • PhD, Université de Technologie de Compiègne, France, 2005.
  • Member of ACM, IEEE, SBC.
  • Human-Computer Interaction, Natural Language Processing, Text Mining, Affective Computing.

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Fabrício Enembreck

  • PhD, Université de Technologie de Compiègne, France, 2003.
  • CNPq Research Productivity Researcher.
  • Multi-Agent Systems, Adaptive Agents, Data Mining.

 

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Jean Paul Barddal

  • PhD, Pontifical Catholic University of Paraná, 2018.
  • Data Mining and Machine Learning on Data Streams, Classification, Regression, Concept Change, Attribute Selection and Clustering.

 

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Júlio César Nievola

  • PhD, Universidade Federal de Santa Catarina, Brazil, 1995.
  • Member of IEEE, ACM.
  • Data Mining, Intelligent Systems, Artificial Neural Networks.

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Rayson Laroca

  • PhD, Universidade Federal do Paraná, 2024.
  • Computer Vision, Machine Learning, and Pattern Recognition.

 

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Vinícius Mourão Alves de Souza

  • PhD, Universidade de São Paulo, Brasil, 2016
  • Data Mining, Machine Learning, Data Stream, Time Series Mining, Smart Sensors.

 

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