Daniel Oberski holds a joint appointment as professor of data science methodology at Utrecht University, department of Methodology & Statistics, and at the University Medical Center Utrecht (UMCU), department of Biostatistics. His work focuses on latent variable modeling and data science applications in the social, behavioral, and biomedical sciences. He leads the social data science team at the national research infrastructure for the social sciences in the Netherlands, ODISSEI. He is also lead data scientist of UMCU’s “digital health” program, which works to implement data science in clinical care at the hospital.
Dr. Laura Boeschoten
Laura Boeschoten is an assistant professor with an interest in measurement errors, missing data and latent variables. Her PhD-research from Tilburg University focused on detecting measurement errors in surveys and introduced a method on how to solve these issues. Currently Boeschoten is working on making data downloads from social media possible to use in research.
Dr. Erik-Jan van Kesteren
Erik-Jan van Kesteren is an assistant professor of applied data science, and researches how to incorporate high-dimensional data into structural equation models. He also works as a part-time programmer at JASP, where he develops easy-to-use interfaces for the wide array of latent variable models available within structural equation modeling.
Dr. Ayoub Bagheri
Ayoub Bagheri is an assistant professor of applied data science at Utrecht University. His PhD-dissertation unites machine learning, text mining and applied data science. His interdisciplinary research contributes to designing decision support systems based on statistical learning algorithms, and to leverage machine learning and text mining methods in application to social sciences and healthcare.
Dr. Anastasia Giachanou
Anastasia Giachanou is a post-doc researcher with an interest in natural language processing, social media analysis and computational social science. Her research interests include fake news detection, bot detection, fact checking, and sentiment analysis. She received her Ph.D. from the Faculty of Informatics at the University of Lugano, in Switzerland, working on the topic of tracking sentiment over time.
Qixiang Fang is a PhD candidate under the supervision of Dr. Daniel Oberski and Dr. Dong Nguyen. His research falls at the intersection of statistics, natural language processing and machine learning, and focuses on improving measurement and causal inference with high-dimensional text data.
Mehran Moazeni is a PhD candidate under supervision of Daniel Oberski and Dr. Emmeke Aarts. His research interests are summarised in applying Machine Learning algorithms alongside Statistical models in the Healthcare domain. Other research interests are pattern recognition, dynamic monitoring, prediction, and latent variable models. Previously he received his master’s in Socioeconomic system analysis, and his thesis was to detect and monitor brain tumours.
Dr. Javier Garcia-Bernardo
Javier Garcia-Bernardo is an assistant professor of social data science. He applies computational models to understand social and economical systems. He is particularly interested in how interactions between agents create and reflect socioeconomical inequalities. Garcia-Bernardo completed his PhD in Political Economy at the CORPNET group (University of Amsterdam), and his MSc in Computer Science at the University of Vermont.
Dr. Mahdi Shafiee Kamalabad
Mahdi Shafiee Kamalabad is an assistant professor of applied data science at Utrecht University. His research interests lies primarily in developing new statistical and machine learning methods for analyzing complex data of complex systems. He has developed various novel models such as (non-homogeneous) Dynamic Bayesian Network Models, and Change point Relational event Model which are flexible enough to analyze various types of time-series data that routinely arise in a variety of disciplines, such as Social and Behavioral Sciences, and Life Sciences. As a Postdoc researcher, Mahdi worked on Modelling of Dynamic Social Networks at Tilburg School of Social and Behavioral Sciences. He received his Ph.D. from the University of Groningen in Applied Statistics.
Dr. Stephanie Eckman
Stephanie Eckman is a Fellow at RTI International conducting research into data quality and the social construction of data. She has a PhD from the Joint Program in Survey Methodology. She visited M&S in Spring 2022.
Thijs Cornelis Carrière finished his Masters in Methodology and Statistics at Utrecht University in 2022. His master thesis focused on using response times as explanation factors for differential item functioning and was part of an internship at Cito, an institute for educational testing. His research interests are on psychometrics, SEM, and use for digital para-data.
Thom Benjamin Volker
Thom Volker is a PhD candidate researching different techniques for creating privacy-preserving synthetic data sets, under the supervision of Dr. Erik-Jan van Kesteren, Dr. Peter-Paul de Wolf and Prof. Dr. Stef van Buuren. He aims to work at the intersection of social-scientific research and cutting-edge statistical techniques, to get the most out of expensively collected research data. His other research interests include multiple imputation for missing data, hypothesis evaluation using Bayes factors and research synthesis.
Dr. Apollinaire Batoure
Apollinaire Batoure is a senior lecturer in Applied Mathematics at University of Ngaoundere, Cameroon. He has a PhD in Decision Support System from University of Ngaoundere. His Postdoc at Utrecht University is based on Fundamentals and Applied Data Science. His research focuses on Time Series Forecasting for Epidemic Preparedness.
For more see his Utrecht University page.
Sofia Chelmi is a Erasmus+ intern working for ODISSEI Social Data Science Team. She completed her bachelor’s degree in Mathematics from the University of Crete. Her research project concerns analyzing co-voting networks in order to detect organized groups in social media.
For more see her Utrecht University page.