Mikel Robredo

PhD of Statistical Data Analysis in Empirical Software Engineering

2023 - Present

University of Oulu, Oulu, Finland

Currently, I am investigating the state-of-the-art data analysis approaches adopted in the Empirical Software Engineering domain. With some scientific articles already published, I am looking forward to publishing a Systematic Literature Review based on my investigation.

Master of Science in Statistical Data Analytics

2021 - 2023

Tampere University, Tampere, Finland

Application of computational statistics within the field of Data Science. Among the disciplines learnt during these studies are Time Series Analysis, Scientific Computing in diverse programming languages, Advanced Statistical Modelling & Bayesian Analysis.

Bachelor of Economics

2016 - 2020

University of the Basque Country, Bilbao, Spain

With a major in Development and International Economics, I developed skills in Statistics, Macroeconomics, Microeconomics and Econometrics. I completed an international mobility of 6 months in the University of Milano-Bicocca, Italy.

Doctoral researcher

2023 - Present

University of Oulu, Oulu, Finland

• Investigation of the state-of-the-art data analysis approaches adopted in the Empirical Software Engineering domain.
• Identification of data analysis issues in the Empirical Software Engineering studies.
• Definition of time dependent statistical analysis techniques.
• Comparison of the new approach with the traditional ones adopted by Empirical Software Engineering studies.
• Internal Validation (application in Empirical Software Engineering do- main with a particular focus on Cohort Study).
• Guidelines definition.

Junior research assistant

2023 (6 months)

University of Oulu, Oulu, Finland

• Data extraction pipeline design for Mining Software Repositories (Python, GitHub REST API).
• Application of Cohort Studies in Empirical Software Engineering with Mature Software project version control data.
• Non-linear regression analysis applying Generalized Linear Models theory (R).
• Scientific writing.