My name is Marilla Bianco and I’m Italian, from Bari (Apulia). I did all my atudies in London, and I graduated in BSc in Criminology and Criminal Psychology at the University of Greenwich, following with a MSc in Mental Health Studies et King’s College London. I am currently doing a PhD in biomedical engineering, University of Messina. By training, I specialise in developmental Science, specifically focused on ASC. My career aim is to work with autistic people, improving clinical research to increase the wellbeing of adults and children. I am fascinated by technological processes of machine learning that I studied through several courses (IBM and Stanford University). Thus, I find the idea of designing intelligent tools investigating early social precursors and biomarkers of autism especially interesting.
In the last decade, the possibility of detecting infants’ early onset of Autism Spectrum Disorder symptomatology has been increasingly taken in consideration. However, currently little is known about the actual implication of early differences in motor and vocal patterns and their connection to a possible ASD onset. This project aims to detect early signs of ASD by analysing infant motor and vocal developmental trajectories through innovative technologies. Thus, the project aims to (1) develop a real-time dynamic multi-person software infrastructure to detect simultaneously human body, hands and facial keypoints on video-sequences and to synchronously extract voice spectrogram; (2) analyse longitudinal motor and vocal repertoires, and parent-infant interaction through data collected by the NIDA Network; (3) Develop a deep-learning-based method and multivariate statistical methods to detect early markers of ASD. The sampling is performed from birth to 12 months, through audio and video recordings of early infant’s behaviours (spontaneous and intentional movements, cry, social attention) and from six to 36 months by the administration of clinical structured instruments according to the developmental age of the infant/child.