Giovanni M. Di Liberto
Giovanni received his Bachelor's degree in Information Engineering in 2011 and his Master's degree in Computer Engineering in 2013, both from the University of Padova, Italy. After a period working on his thesis at University College Cork (UCC, Ireland), he joined Edmund Lalor's research lab in Trinity College Dublin where he pursued a PhD in auditory neuroscience in the School of Electronic and Electrical Engineering. He received his PhD in 2017 and he joined the Laboratoire des Systèmes Perceptifs at École Normale Superieure (Paris) immediately after, under the supervision of Alain de Cheveigné and Shihab Shamma. Then, he briefly continued his work on speech communication with Richard Reilly as a postdoctoral researcher (TCD), while also working with Simon Kelly at UCD, expanding his expertise into the Decision Making domain. He holds the title of Assistant Professor in Intelligent Systems in the School of Computer Science and Statistics at Trinity College Dublin.
Giovanni's scientific interests centre on understanding the brain mechanisms underlying speech comprehension. In his work, he develops data analysis methods and applies them to brain data to identify the neural processes responsible for the transformation of a sensory stimulus into its abstract meaning. Brain electrical data is measured with either non-invasive (e.g., electroencephalography - EEG) or invasive (e.g., electrocorticography - ECoG) technologies. The first aspect of his research is methodological and has produced novel experimental and analysis frameworks to investigate cortical auditory processing. The second aspect of his research is to use such novel methods to test theories on auditory perception, such as the hierarchical processing of speech and predictive processing theories (e.g. predictive coding). Finally, the third part of his work is translational and involves the identification of solutions to utilise his novel methods in applied settings, for example as tools to develop brain-computer interfaces (COCOHA project) or as objective measures for the monitoring of language development and healthy ageing.
Current positions
Teaching
2023-24
- Introduction to Machine Learning - CSP7000 (coordinator; MSc in Smart and Sustainable Cities)
- Machine Learning - CS7CS4 (co-teaching; MSc in Computer Science - Data Science)
- Introduction to Machine Learning - CSP7001 (coordinator; PG Diploma in Applied Social Data Science)
2022-23
- Introduction to Machine Learning - CSP7000 (coordinator; MSc in Smart and Sustainable Cities)
- Machine Learning - CS7CS4 (co-teaching; MSc in Computer Science - Data Science)
- Introduction to Machine Learning - CSP7001 (coordinator; PG Diploma in Applied Social Data Science)
2021-22
- Introduction to Machine Learning - CSP7000 (design and coordinator; MSc in Smart and Sustainable Cities)
- Introduction to Machine Learning - CSP7001 (design and coordinator; PG Diploma in Applied Social Data Science)
Past positions