Our key research interests lie in mathematical psychology, psychometrics, psychological assessment and cognitive modelling.
Our research aims to investigate psychological theories under the lens of wrangling, manipulating and modelling psychological data through powerful quantitative techniques drawn from different fields, such as artificial intelligence, multivariate data analysis, Bayesian statistics, latent variable modelling, research synthesis and network science. Our studies rely on mathematical and computational frameworks where psychological data can be investigated in view of relevant psychological theories and compared against suitable reference models. Emphasis is placed not only on understanding psychological data through models but also on enhancing our understanding of psychological phenomena through quantitative psychometric measurements
A key research line of this group is devoted to mathematical psychology and cognitive processing for designing inference mechanisms able to detect faking through psychometric scales, with applications ranging from academic fraud detection to best practices.
Another key research line is artificial psychometrics, which extracts quantitative features from knowledge graphs and multilayer cognitive networks to infer the prevalence of psychological constructs within human-centered, interpretable AIs.
We also devote our attention to structural equation modelling (SEM) and longitudinal data analysis, merging advanced statistical and data science techniques for achieving personality assessment and for adopting organisational research methods.
Finally, our group is also interested in the development and application of theory-driven, data-driven, and emerging hybrid approaches for psychology and cognitive science.