Zeno’s PhD project focuses on developing a predictive modeling framework called Stacked Domain Learning that can be used for theory development in interdisciplinary research when data are collected from multiple research domains. The goal is to combine domain-specific theories based on predictive accuracy to develop an interdisciplinary theory. A particular strength of the methodological approach is that the unique domain-specific data characteristics and theories are taken into account. Furthermore, by shifting the focus to predictive accuracy, theories can be formed that are more generalizable to new samples and therefore more applicable in applied contexts where real-world problems require methods that ensure reliable predictions.
Photo: Alexander Santos Lima