Jean Paul Barddal

Graduate Program in Informatics (PPGIa), Pontifícia Universidade Católica do Paraná (PUCPR).


Office 8, Building 8

R. Imaculada Conceição, 1155

Curitiba, Paraná, Brazil

+55 41 3271-1351

I’m an Associate Professor with the Knowledge Discovery and Machine Learning (DCAM) of Graduate Program in Informatics (PPGIa) at the Pontifical Catholic University of Paraná (PUCPR). My research focuses on machine learning, more specifically on data stream mining. More specifically, I’m currently working on the following topics:

  • Supervised learning: data stream classification and regression
  • Unsupervised learning: data stream clustering and outlier detection
  • Data pre-processing: how to handle high-dimensionality, text data, etc, on streaming data
  • Distributed stream processing

If you’re also interested in any of the topics above, either in theoretical or applied ends, and you would like to pursue a degree or collaborate, feel free to drop me a message using the link below. Also, feel free to check my Lattes CV here (in Portuguese).

selected publications

    Adaptive Learning on Hierarchical Data Streams using Window-weighted Gaussian Probabilities
    Eduardo Tieppo, Julio Cesar Nievola, and Jean Paul Barddal
    Applied Soft Computing 2024
  2. STATS. & COMP.
    Random Forest Kernel for High-Dimension Low Sample Size Classification
    Lucca Portes Cavalheiro, Simon Bernard, Jean Paul Barddal, and Laurent Heutte
    Statistics and Computing 2023
  3. ICMLA
    Detecting Relevant Information in High-Volume Chat Logs: Keyphrase Extraction for Grooming and Drug Dealing Forensic Analysis
    Jeovane Honório Alves, Horácio A. C. G. Pedroso, Rafael Honorio Venetikides, Joel E. M. Koster, Luiz Rodrigo Grochocki, Cinthia Obladen Almendra Freitas, and Jean Paul Barddal
    In International Conference on Machine Learning with Applications (ICMLA) 2023
    Incremental Specialized and Specialized-Generalized Matrix Factorization Models based on Adaptive Learning Rate Optimizers
    Antônio David Viniski, Jean Paul Barddal, and Alceu Souza Britto Jr.
    Neurocomputing 2023
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