Advances in computational power and statistical algorithms, in conjunction with the increasing availability of large datasets, have led to a Cambrian explosion of machine learning (ML) methods. For population researchers, these methods are useful not only for predicting population dynamics but also as tools to improve causal inference tasks. However, the rapid evolution of this literature, coupled with terminological disparities from conventional approaches, renders these methods enigmatic and arduous for many population researchers to grasp.
This workshop on November 5 to 6, 2024 at the Max Planck Intsitute for Demographic Research (MPIDR) in Rostock, Germany, clarifies the goals, techniques, and applications of machine learning methods for population research.
This in-person workshop will take place in November 5-6 at the Max Planck Institute for Demographic Research in Rostock. We invite population researchers with interest in ML applications. We aim to receive contributions from different fields of population sciences, such as population health, formal and social demography, public health and economics, among others.
We invite submission of original research abstract with relevance to ML and population sciences (max 500 words) and a CV (max. one page) to
Submission Deadline: 30 April 2024
