Some extra works:

  • Participation in the National Statistic Meeting (ENESTE) - 2018;

  • Participation as organizing committee of the National Meeting of Statistics (ENESTE) - 2019;

  • Participation as organizing committee of the Paraiba Sampling Meeting (EPA) - 2019;

  • Short course Package ggplot2 and dplyr of software R (Department of Social Sciences, UFPB, João Pessoa / PB) - 2019;

  • Statistics applied in Free Softwares - GIT / GITHUB, by the Federal University of Paraíba - 2019;

  • Scientific Initiation Scholarship for undergraduate students in Statistics (first year), 2019 - 2020;

  • Creation of a page for easy access to the databases of responses to stored IRT models, in a similar way, for free access to the implemented code referring to the project of the first year of scientific initiation - 2020;

  • Co-authorship of the article entitled Γ-IRT: A Novel Item Response Model for positive Continuous Response, submitted to the magazine Expert Systems with - 2020;

  • Python course for Data Science and Machine Learning - Udemy, 2020;

  • Tensorflow 2.0 Course: A Complete Guide to the new TensorFlow - Udemy, 2020;

  • Founding member of TAIL - Technology and Artificial Intelligence League, director of mathematics - 2020.

  • System Developer in the CICC-PB Integration Project (AI + Data Science) - 2020.

    • Partners: Brisanet, Hikivision, FUNETEC, SEFAZ, SESDS and SEECT.

    • Objective: To design and develop a data integration platform related to the systems of the Integrated Command and Control Center (CICC) of the Government of the State of Paraíba (CICC-PB) and current systems of the State Department of Finance of the State of Paraíba (SEFAZ ), Paraíba State Secretariat for Security and Social Defense (SESDS) and Paraíba State Secretariat for Education and Science and Technology (SEECT), including real-time data and building applications that use intelligence with the main objective of improving tax inspection systems; public security; and education, culture and technology, linked, respectively, to SEFAZ, SESDS and SEECT.

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