Elisabetta is a lecturer at Queen Mary University of London, where she leads the Comparative Cognition Lab. After gaining her PhD at University of Trieste (Italy), she worked in animal behaviour and cognition, neuroscience and population genetics. Her research interests are focused on the building blocks of cognition, that she investigates using domestic chicks, tortoises and insects as models. The comparison between species and evolutionary perspective offer several advantages in understanding different strategies in early social behaviour, fast learning (e.g. filial imprinting), artificial grammar learning, lateralisation and other features that enable animals to make fast and effective decisions without intensive training.
Elisabetta is interested in using insights derived from behavioural mechanisms observed in animals to improve artificial intelligence and machine learning, and in developing robotic systems that interact with animals. Her work aims at clarifying what enhances and what hinders behavioural and cognitive performance.
Elisabetta is pursuing three main lines of research as a Turing Fellow: (a) how to use biological insights (e.g. learning mechanisms as filial imprinting and predisposed knowledge that does not depend on learning) to improve artificial intelligence; (b) developing robots capable of interacting with animals systems; (c) understand the minimal computational requirements for rule learning and artificial grammar learning.