Current researchMy methodological work focuses on combining sequence analysis and probabilistic modelling and developing methods for simulating complex social sequence data e.g., residential, employment, and family trajectories that are studied in parallel, with the aim of studying effects of interventions on individuals' trajectories. In addition to the methodological work I am collaborating with Juta Kawalerowicz on analysing life histories of political candidates and with Benjamin Jarvis on residential trajectories and neighbourhood segregation.
Previous researchI completed my PhD in statistics at the University of Jyväskylä in Finland in 2016. In my thesis I compared different statistical methods - sequence analysis, event history analysis, and hidden Markov models - for the analysis of complex life course data. These methods were described and tested with empirical analyses, e.g., to study which types of joint family and career trajectories are typical and which atypical with Mervi Eerola, to find associations between individuals' childhood characteristics and their future partnership trajectories with Fiona Steele, Katja Kokko, Eija Räikköinen, and Mervi Eerola, and to compress information across various life domains into more general life stages with Jouni Helske and Mervi Eerola.
In addition to the thesis the PhD resulted in an R package called seqHMM which is free software for analysing and visualizing categorical sequence data with (mixture) hidden Markov models (with Jouni Helske).
Following my PhD I worked as a post doc in the Multigenerational Demography group in the Department of Sociology at the University of Oxford, working on transmission of education. My research was focused on educational reproduction and the role of childhood family events in the multigenerational transmission of education with Richard Breen and John Ermisch.