Perseverence Savieri
  • Laarbeeklaan 101

    1090 Brussels


  • Pleinlaan 2

    1050 Brussel


  • Source: Scopus
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Research interests

Perseverence Savieri obtained his Master of Science: Biostatistics at Stellenbosch University, South Africa. He is currently pursuing a PhD in Medical Sciences, titled “An artificial intelligent consultant to enhance statistical thinking”.

 Summary of the Project:

Statistical consultants frequently encounter researchers seeking support for their study design and data analysis. Such requests for support often encompass doubts in terms of the type of analysis warranted. Although academic researchers obtained specific training in quantitative courses, the lack of hands-on experience often makes researchers feel uncomfortable with respect to statistical choices and their data analysis.

In this project, we intend to develop an artificial intelligence (AI) system to provide feedback to the researcher. Given a data set, the system will analyse data properties and characteristics. By rendering specific visualisations together with proper scientific context and references, the researcher will obtain feedback to critically assess their data and the related statistics to enhance the scientific process. In particular, the project will concentrate on aspects where non-statisticians are known to doubt about and struggle with such as residual diagnostics to verify regression assumptions, dealing with collinearity and dimension reduction, choosing covariance structures among other aspects. The tools will be interactive web applications built from the Shiny package within the statistical R environment. The apps will not be exhaustive but will provide the necessary scientific tutoring, references and reflections for a specific statistical technique/assumption which are considered healthy thinking approaches.

This PhD research will facilitate and enhance the methodological support towards the research community at the Vrije Universiteit Brussel as well as the medical academic hospital UZ-B. Furthermore, the project contributes scientifically to the computational field within (applied) statistics where artificial intelligence as well as machine learning are renewing and innovating the statistical field.


Data Analysis • Data Management • Data Visualization • Statistical programming & modelling

Proficient in the following statistical softwares:  R, STATA, SAS, SPSS.

Education/Academic qualification

Biostatistics, Master of Science, University of Stellenbosch

1 Feb 20191 Dec 2020

Award Date: 30 Mar 2021

Statistics and Mathematics, Bachelor of Science, Honours, University of Zimbabwe

1 Sep 201030 Jun 2014

Award Date: 12 Sep 2014


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