Population and Social Data Science Summer Incubator Program 2026
The Max Planck Institute for Demographic Research (MPIDR) is inviting applications from qualified and highly motivated students for a Summer Research Visit.
The goal of the Population and Social Data Science Summer Incubator Program is to enable discovery by bringing together data scientists and population scientists to work on focused, intensive and collaborative projects of broad societal relevance.
For a period of 3 months (June 8th – August 21st, 2026) participating students will work in small teams, with support from experienced mentors, towards a common research goal. For the summer of 2026, the focus of the program will be on two main research areas:
01.
Spatial Mobility and Scientific Production
02.
Digitalization, AI, and Inequalities

Spatial Mobility and Scientific Production
01
Mentors
Aliakbar Akbaritabar
Aliakbar Akbaritabar (Ali) is an Assistant Professor of Computational Social Science at the Institute of Sociology and Demography of the University of Rostock and a Research Scientist at the Max Planck Institute for Demographic Research. Ali is a computational social scientist with a background in sociology. His work focuses on themes related (but not limited) to science of science, scholarly and high-skilled migration, social networks, collaboration networks, and computational social science.
Andrés Castro
Andrés Castro is a sociologist, demographer, and computational social scientist. He leads the Science and Technology Studies unit at the Computational Social Science and Humanities Laboratory of the Barcelona Supercomputing Center (CSSH - BSC). His research focuses on global inequalities in knowledge production, bibliometric analysis, and research assessment. As a demographer, he does research on family dynamics with a focus on global South immigrants in global North locations.
Irena Chen
Irena Chen is a Research Scientist in the Department of Digital and Computational Demography at MPIDR. Her research interests include Bayesian hierarchical models, correlated time series, and latent variable methods with applications in demography, epidemiology, and precision medicine. She received a PhD in Biostatistics from the University of Michigan.

Digitalization, AI, and Inequalities
02
Mentors
Carolina Coimbra Vieira
Carolina Coimbra Vieira is a Postdoctoral Research Scientist at Max Planck Institute for Demographic Research. Previously, she was a PhD Student in Computer Science at Universität des Saarlandes also affiliated to the Max Planck Institute for Demographic Research and the Max Planck Institute for Software Systems. She received her B.Sc. and M.Sc. in Computer Science from Federal University of Minas Gerais (UFMG) in Brazil. Carolina’s research focuses on interdisciplinary topics at the intersection of computer science and the use of digital trace data to study migration, culture, inequalities, and algorithmically-mediated user engagement on social media platforms.
Megan Evans
Megan Evans is a postdoctoral researcher at the Max Planck Institute for Demographic Research. She obtained her PhD in Sociology and Demography at Pennsylvania State University. Her research investigates the social processes that perpetuate place-based inequalities and shape racial disparities, with a particular focus on how race, space, and technology intersect to reinforce social stratification. By integrating advanced computational methods and big data with social science theory, her research bridges micro-level cognitive and behavioral patterns to macro patterns of spatial inequality, advancing our understanding of how technology and institutional practices shape contemporary urban inequality.
Nkechi S. Owoo
Nkechi S. Owoo is a Professor of Economics at the University of Ghana, with over a decade of research and mentorship experience in gender economics, labour markets, and economic inclusion across Africa. She holds a PhD in Economics from Clark University, M.A., U.S.A.
Emilio Zagheni
Emilio Zagheni is Director of the Max Planck Institute for Demographic Research. He is best known for his research on combining digital trace data, traditional sources, and new forms of data collection, within solid statistical and formal demographic frameworks, in order to advance population science. In his various professional capacities, he has played a key role in favoring collaboration and exchange between demographers, statisticians and computer scientists.