Lasai Barreñada


Jorge Fernadez Calatrava, Lasai Barreñada and Juan Carlos Gálvez were awarded the 2nd prize in the 2022 IAOS Young Statisticians Prize competition with their manuscript: Timeliness reduction on Industrial turnover index based on Machine Learning algorithms.

This manuscript will be published in the Statistical Journal of the IAOS, Vol38 (2022), issue 4.

Awarded the 2nd prize in the 2022 IAOS Young Statisticians Prize competition (with Juan Carlos Gálvez and Jorge Fernadez Calatrava)

Invited to make a statement on Young Statisticians/Official Statistics Lasai stated:

Official statistics are the backbone of the informed society, hence the democracy. For this reason, it is very important that official statisticians focus not only on the production and dissemination of official statistics bust also in the research and development of novel methodologies. Without this research the quality will not match the standards of the society and the statistics will lose relevance. I think that YSP is a great initiative to motivate young statisticians to conduct research and to promote their work. Even if you do not win just by participating, I believe that you will increase your knowledge incredibly.


Lasai Barreñada hold an EMOS (European master in official statistics) finished in 2021. He started working in Statistics Spain in November 2020 with a postgraduate scholarship where he has been in the SDG department. He was  always interesten in new innovative methodologies and for this reason he joined the BCAM (Basque centre of applied Mathematics) as a researcher in machine learning for COVID-19 prognosis. In this job he has  build machine learning models with real health data to predict the risk probability of a COVID-19 patient when entering a hospital.

He is currently a PhD candidate in KU Leuven, working in the creation and validation of clinical models to diagnose ovarian tumours with the International Ovarian Tumor Analysis (IOTA) group