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General Information

Full Name Jean Paul Barddal
Languages Portuguese, English

Education

  • 2018
    Ph.D. in Informatics
    Pontifícia Universidade Católica do Paraná, Curitiba, Brazil
    • My PhD thesis was on Feature Selection for Data Stream Classification.
    • You can find a copy of my thesis here
  • 2015
    M.Sc. in Informatics
    Pontifícia Universidade Católica do Paraná, Curitiba, Brazil
    • My Master's dissertation was on Data Stream Clustering.
    • You can find a copy of my dissertation here
  • 2015
    Apple Developer Academy (former BEPiD)
    Hosted by the Pontifícia Universidade Católica do Paraná, Curitiba, Brazil
  • 2013
    B.Sc. in Computer Science
    Pontifícia Universidade Católica do Paraná, Curitiba, Brazil
    • Awarded with the Marcelino Champagnat academic merit prize (GPA 9.6)

Experience

  • 2019 - current
    Professor
    Pontifícia Universidade Católica do Paraná
    • Researcher with the Graduate Program in Informatics (PPGIa)
    • Lecturer with the Computer Science, Information Systems, Cybersecurity, and Software Engineering undergraduate degrees.
  • 2017 - 2023
    Co-Founder, Machine Learning Engineer, DPO
    4KST
    • Development of novel techniques for applied machine learning, in particular towards financial applications.
    • Definition and implementation of information security technologies.
    • Implementation of a C/C++ software for data stream mining.
  • 2019 - current
    Associated Researcher
    Advanced Institute for Artificial Intelligence (AI2)
    • The Advanced Institute for Artificial Intelligence (AI2) is a consortium of researchers committed to openness and inclusiveness that gathers together different experts in AI with a collaborative and constructive spirit to boldly attack challenging problems with high social and economic impact through the fundamental support of the private sector. More information about AI2 can be found here.
  • 2021 - 2022
    CNPq RHAE Scholar
    CNPq/SEMPI/MCTI
    • In this project, I developed a C/C++ software for data stream classification. This software encompasses several learning task formats, classifiers, and evaluation metrics. It also provides single-thread, multi-thread and GPU support.
  • 2016 - 2020
    Project Reviewer
    Udacity
    • Ad-hoc project reviewer and mentor for the Data Analysis, Predictive Analytics for Business, Machine Learning, and Deep Learning nanodegrees.

Research Visits

  • 2021
    Laboratoire d'Informatique, de Traitement de l'Information et des Systèmes (LITIS)
    • Visitor researcher as per invitation of Professor Laurent Heutte.
  • 2017
    Télécom ParisTech
    • Visitor researcher under the supervision of Prof. Albert Bifet on Big Data Stream Mining.
    • Funded by CAPES via a PDSE grant.
  • 2016
    University of Waikato
    • Visitor researcher under the supervision of Prof. Bernhard Pfahringer on Data Stream Mining.
    • Funded by the hosting University.

Conference PC Membership

    • Online Recommender Systems and User Modeling, ACM Conference on Recommender Systems (RecSys)
    • International Joint Conference on Neural Networks (IJCNN)
    • IEEE International Conference on Tools with Artificial Intelligence (ICTAI)
    • ACM Symposium on Applied Computing (ACM SAC)
    • International Joint Conference on Artificial Intelligence (IJCAI)
    • Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD)
    • Asian Conference on Intelligent Information and Database Systems
    • FiCloud, The IEEE 6th International Conference on Future Internet of Things and Cloud
    • Large-scale Learning from Data Streams in Evolving Environments (LEARNSTREAM)

Journal Refereeing

    • International Journal of Data Science and Analytics
    • Knowledge-based Systems
    • Neurocomputing
    • IEEE Transactions on Cybernetics
    • Software, Practice and Experience
    • Theoretical Computer Science
    • Information Sciences
    • Neural Computing & Applications
    • IEEE Transactions on Parallel and Distributed Systems
    • Pattern Recognition
    • IEEE Transactions on Knowledge and Data Engineering
    • Journal of Communication and Information Systems
    • IEEE Access
    • Machine Learning
    • Knowledge and Information Systems
    • Future Generation Computer Systems - The International Journal of eScience
    • Computational Intelligence (Online)
    • Springer Nature Applied Sciences
    • Computer Applications in Engineering Education

Open Source Projects

  • current
    Massive Online Analysis (MOA)
    • MOA is a great tool for developing and testing data stream mining algorithms.

Honors and Awards

  • 2022
    • Honored Professor (Computer Science B.Sc. Degree) - 2nd semester
    • Honored Professor (Computer Science B.Sc. Degree) - 1st semester
    • PPGIa/PUCPR: Awarded with the paper with the biggest research impact
    • Awarded with the Excellence in Scientific Research - Q1 prize
    • Awarded as one of the best-ranked lecturers at PUCPR - Prêmio de Excelência no Ensino
    • Awarded as one of the best-ranked lecturers at PUCPR - Prêmio de Excelência em Pesquisa
  • 2021
    • PPGIa/PUCPR: Awarded with the paper with the biggest research impact
    • Awarded with the Excellence in Scientific Research - Q1 prize
  • 2020
    • Awarded as one of the best-ranked lecturers at PUCPR - Prêmio de Excelência no Ensino
    • Awarded with the Excellence in Scientific Research - Q1 prize
  • 2019
    • PPGIa/PUCPR: Awarded with the paper with the biggest research impact
    • Awarded with the Excellence in Scientific Research - Q1 prize
    • Awarded as one of the best-ranked lecturers at PUCPR - Prêmio de Excelência no Ensino
  • 2013
    • Marcelino Champagnat academic merit prize with a GPA 9.6 out of 10.0

Grants

  • 2022
    • CNPq: Uma abordagem de aprendizagem de máquina para previsão de taxas de inadimplência e intenção de recuperação de crédito (R$ 647,691.00)
  • 2019
    • Fundação Araucária/Renault #06/2019 (R$33,600.00)
    • Accelerated Data Science Program (NVIDIA) - NVIDIA Titan V GPU

Current Advisees

  • 2022
    • (PhD - advisor) Cristiano Garcia. Detecção de Mudança de Conceito em Data Streams Textuais.
    • (PhD - advisor) Antonio David Viniski. Descoberta de Padrões no Cruzamento de Dados de Perfis de Consumo e Patológico.
    • (PhD - coadvisor) Sheila Cristiana de Freitas. Método de Análise de Detecção de Concept Drift em Processos com Foco na Qualidade dos Modelos Descobertos.
    • (PhD - coadvisor) Eduardo Tieppo. Classificação Hierárquica em Data Streams.
    • (MSc - coadvisor) Caio da Silva Dias. Pattern Spotting using Deep Learning.
    • (MSc - coadvisor) Antonio Michel Ferreira dos Santos. Adaptação a Mudanças de Conceito Usando Redes Neurais.
    • (MSc - coadvisor) André Seiji Suzuki Kusakariba. TBD.
    • (MSc - coadvisor) Luciano Mauda Jr. Contribuicao de algoritmos de recomendação para avaliação de estudantes de ensino fundamental
    • (BSc - advisor) Allan Oliveira Braun. Aplicação de Fatores de Decaimento em Sistemas Adaptativos de Recomendação.
    • (BSc - advisor) Gabriel Przytocki. Aplicação de Fatores de Decaimento em Sistemas Adaptativos de Recomendação.
    • (BSc - advisor) Patrick Caetano. Extração de Palavras-Chave em Chats de Dispositivos Móveis em Análises Periciais.
    • (BSc - advisor) Horácio Aaron C. G. Pedroso. Extração de Palavras-Chave em Chats de Dispositivos Móveis em Análises Periciais.
    • (Scientific Initiation) Enzo Bottan Coutinho. RANDOM FOREST EM GPU PARA CLASSIFICAÇÃO EFICIENTE DE BIG DATA STREAMS EM FORMATO MINI-BATCH.
    • (Scientific Initiation) Gabriel de Castro Ezequiel. ANÁLISE DE MUDANÇAS DE CONCEITO EM DATASETS REAIS.

Former Advisees

  • 2022
    • (MSc - advisor) Vinicios Cainã dos Santos Coelho. CLASSIFICAÇÃO DE FLUXOS CONTÍNUOS DE DADOS DESBALANCEADOS USANDO ENSEMBLES HETEROGÊNEOS, SUB E SOBRE-AMOSTRAGEM INVERSA ALEATÓRIA E META-APRENDIZAGEM.
    • (MSc - advisor) João Gabriel Corrêa Kruger. Uma Abordagem de Aprendizagem de Máquina Explicável para Previsão de Evasão Estudantil.
    • (MSc - advisor) Eric Kenzo Taniguchi Onuki. Bringing Awareness to Energy Consumption in Data Stream Mining.
    • (PhD - coadvisor) Denise Maria Vecino Sato. Mineração de processo sobre stream de dados.
  • 2021
    • (MSc - advisor) Lucca Portes Cavalheiro. DYNAMIC SELECTION OF CLASSIFIERS IN DATA STREAMS.
    • (MSc - coadvisor) Eduardo Ferreira José. DESENVOLVIMENTO DE TÉCNICAS DE APRENDIZAGEM PERSONALIZADA ADAPTATIVA PARA SISTEMAS INCREMENTAIS DE RECOMENDAÇÃO.
    • (BSc - advisor) André de Macedo Wlodkovski. t-SNE Paramétrico em Classificação de Data Streams de Alta Dimensionalidade.
    • (BSc - advisor) Kalebe Rodrigues Szlachta. t-SNE Paramétrico em Classificação de Data Streams de Alta Dimensionalidade.
    • (BSc - advisor) Bruno Thuma. Comparativo de Técnicas de Feature Extraction a partir de Data Streams Textuais.
    • (BSc - advisor) Pedro Silva de Vargas. Comparativo de Técnicas de Feature Extraction a partir de Data Streams Textuais.
  • 2020
    • (BSc - advisor) Jean Paulo dos Santos Filho. Um plug-in para Visualização de Árvores de Decisão e Extração de Importância de Atributos para o Massive Online Analysis.
    • (BSc - advisor) Luan Patrick Alves Poi. Desenvolvimento de um Bot de Análise e Operação de Swing Trade na Bolsa de Valores.
    • (Scientific Initiation) Luã Enrique Zangrande. ​IMPLEMENTAÇÃO DE XGBOOST EM GPU PARA CLASSIFICAÇÃO EFICIENTE DE BIG DATA STREAMS.
    • (Scientific Initiation) Marcos Antonio Correia Junior. Mineração Pseudo-distribuída de Big Data Streams Usando Apache SAMOA.
    • (Scientific Initiation) Yerik Rudolf Kowlowski. Otimização do cálculo de métricas de avaliação para sistemas adaptativos de recomendação.
  • 2019
    • (Scientific Initiation) Mateus Gomes Pimenta. MINERANDO BIG DATA STREAMS COM O APACHE SPARK STREAMING.
    • (Scientific Initiation) Oscar Henrique Lucas Henrichs. MINERANDO BIG DATA STREAMS COM O APACHE SAMOA E INFRA-ESTRUTURA APACHE STORM.