Speakers at the Summer School in Statistics 2023

Ton de Waal

Ton de Waal studied mathematics at Leiden University and Eindhoven University of Technology. In 1993, he started to work at Statistics Netherlands, where he currently is senior methodologist. He obtained his PhD degree in 2003. Since 2014, Ton is also professor in Data Integration at Tilburg University. He is co-author of two books on statistical disclosure control and one book on statistical data editing and imputation. His current fields of interest include imputation of missing data, correction for measurement error, correction for selection error, correction for linkage error, combining estimates for probability and nonprobability samples, statistical matching, and measuring quality of multisource statistics.

Natalie Shlomo

Natalie Shlomo is Professor of Social Statistics at the University of Manchester and publishes widely in the area of survey statistics, including small area estimation, adaptive survey designs, non-probability sampling, confidentiality and privacy, data linkage and integration. She has over 70 publications and refereed book chapters and a track record of generating external funding for her research. She is an elected member of the International Statistical Institute (ISI), a fellow of the Royal Statistical Society and   a fellow of the Academy of Social Sciences. She is President of the International Association of Survey Statisticians 2023-2025.  She also serves on national and international Methodology Advisory Boards at National Statistical Institutes and on several editorial boards. Homepage:   https://www.research.manchester.ac.uk/portal/natalie.shlomo.html

Jacco Daalmans

Jacco Daalmans (1977) is a methodologist at Statistics Netherlands with a broad interest in research domains, like macro integration, data editing, imputation, combining data sources and the consumer price index. In 2019 he graduated with a PhD from Tilburg University with a thesis on applications of macro integration in official statistics.

Sander Scholtus

Sander Scholtus (1983) works as a methodologist at Statistics Netherlands. His main research interests are in data editing, imputation, combining data sources and estimation of accuracy under sampling and non-sampling errors. He obtained a PhD from VU University Amsterdam in 2018 with a thesis on methods for automatic data editing and modelling measurement errors.

Danila Filipponi

Dr. Danila Filipponi holds a Ph.D. in Statistics from the University of Pescara and a Master's degree in Statistics from Penn State University. She has held various positions at ISTAT since joining the organization in 2000. Throughout her career, Dr. Filipponi has played a central role in the development and implementation of methodologies for the 2001 and 2011 Italian Economic Census. Furthermore, she has served as the head of the unit responsible for integrating and assessing the quality of administrative data. She has been extensively involved in establishing the methodologies for implementing the Italian Business Register and Labor Register, utilizing both administrative and survey data. Currently, Dr. Filipponi holds the position of head of a specialized unit dedicated to defining standards and methods for producing statistics in a multisource scenario. Her leadership and expertise contribute significantly to ensuring the production of accurate statistical output across different sectors of ISTAT.

Roberta Varriale

Roberta Varriale is assistant professor at La Sapienza University of Rome since November 2022. After getting the PhD in Applied Statistics at the University of Florence in 2008, she worked as researcher at the University of Tilburg and the University of Florence. Since 2011, she was a researcher in methodology and statistics at the Italian national institute of Statistics (Istat). In Istat, she mainly worked in data editing and imputation, and for the design of multi-source statistical processes to develop and support the system of statistical registers. She was responsible for the design and implementation of the Register for Public Administration. Since 2020, she was an Istat member of the Advisory Committee for statistical methodologies. In her research, she developed methodologies using latent variable models both for producing statistics using different data sources, and for editing and imputation and estimation phases, and she worked on methodologies for assessing the quality of multi-source production processes. Nowadays, she works on latent variable models and machine learning tools for producing statistics in a multisource context. Her work has been presented at numerous national and international conferences and published in national and international journals and book chapters.