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Teaching Staff

Biography

Fernando Reis is an Invited Lecturer at NOVA Information Management School (NOVA IMS) in the field of big data and official statistics. He has a degree in Economics from the Faculty of Economics of the New University of Lisbon, with a specialization in econometrics. He was a senior statistician at the National Statistics Institute of Portugal (INE) between 1997 and 2003. Since 2004 he has been an official at Eurostat (European Commission), the statistical office of the European Union. After working for several years in the production of official statistics, since 2011 he has been dedicated to methodological development, first in the modernization of social statistics, in particular in the integration of household surveys, and since 2014 in the use of big data for the production of official statistics. In the big data domain, Fernando Reis did research on the use of data from mobile phone operators and the World Wide Web for statistical purposes. He also addressed broader questions about the impact of big data for official statistics and methodological developments such as the correction of selectivity in big data sources and quality frameworks.

Scientific Publications

Descy, P., Kvetan, V., Wirthmann, A., & Reis, F. (2019)

Towards a shared infrastructure for online job advertisement data. Statistical Journal of the IAOS, 35(4), 669-675.

Ricciato, F., Wirthmann, A., Giannakouris, K., Reis, F. & Skaliotis, M. (2019)

Trusted smart statistics: Motivations and principles. Statistical Journal of the IAOS, 35(4), 589-603.

Ricciato, F., Wirthmann, A., Skaliotis, M., Reis, F., & Giannakouris, K. (2019)

Deep data and shared computation: Shaping the future Trusted Smart Statistics. In Proc. conference on New Techniques and Technologies for Statistics.

Beręsewicz, M., Lehtonen, R., Reis, F., Di Consiglio, L., & Karlberg, M. (2018)

An overview of methods for treating selectivity in big data sources. Eurostat Statistical Working Paper. Doi: https://doi. org/10.2785/312232.

Vanhoof, M., Reis, F., Ploetz, T., & Smoreda, Z. (2018)

Assessing the quality of home detection from mobile phone data for official statistics. arXiv preprint arXiv:1809.07567.

Vanhoof, M., Reis, F., Smoreda, Z., & Ploetz, T. (2018)

Detecting home locations from CDR data: introducing spatial uncertainty to the state-of-the-art. arXiv preprint arXiv:1808.06398.

Debusschere, M., Lusyne, P., Dewitte, P., Baeyens, Y., De Meersman, F., Seynaeve, G., ... & REUTER, H. (2017)

Big data et statistiques: un recensement tous les quarts d’heure. Bruxelles, Direction générale statistique–Statistics Belgium.

Ioannidis, E., Merkouris, T., Zhang, L. C., Karlberg, M., Petrakos, M., Reis, F., & Stavropoulos, P. (2016)

On a Modular Approach to the Design of Integrated Social Surveys. Journal of Official Statistics (JOS), 32(2).

Agafiţei, M., Gras, F., Kloek, W., & Reis, F. (2015)

Measuring output quality for multisource statistics in official statistics: some directions. Statistical Journal of the IAOS, 31(2), 203-211.

Karlberg, M., Reis, F., Calizzani, C., & Gras, F. (2015)

A toolbox for a modular design and pooled analysis of sample survey programmes. Statistical Journal of the IAOS, 31(3), 447-462.