POSITIONS:
Full Professor (Psychology and Artificial Intelligence), University of Padova (Italy)
Senior Research Associate, IRCCS San Camillo Neurorehabilitation Hospital, Venice-Lido (Italy)

EDUCATION:
Laurea (MSc) in Experimental Psychology, University of Padova, Padova (Italy), 1994.
European Diploma in Cognitive Science, International School for Advanced Studies (SISSA), Trieste (Italy), 1997.
Ph.D. Experimental Psychology, University of Trieste, 1999.

PREVIOUS PROFESSIONAL EXPERIENCE:
• Research Fellow, University College London (UK), 1994-1998.
• Visiting Scientist, Macquarie University, Sydney (Australia), 1998.
• Research Fellow, University of Padova, 1999-2000.
• Assistant Professor, Università Vita-Salute San Raffaele, Milan, 2000-2001
• Associate Professor, University of Padova, 2001-2006
• Full Professor, University of Padova, since 1/12/2006
• Invited Visiting Professor, Aix-Marseille University (France), 2011
• Director, Center for Cognitive Science, University of Padova, 2008-2012

AWARD AND GRANTS:
ERC laureate (2008, Starting Grant for Frontier Research from the European Research Council)
Best PhD Thesis in Psychology Award (1999) from the Italian Psychological Association (AIP)
Principal investigator in many projects funded by public and private bodies (European Commission, European Research Council, McDonnell Foundation USA, Italian Ministry of Research, Italian Ministry of Health, Cariparo Foundation, Compagnia di San Paolo Foundation; Wellcome Trust, UK; Royal Society of London, UK).

INSTITUTIONAL BOARDS:
• Chair of Research Committee and Budget Committee of the Department of General Psychology
• Member of the Executive Board of Padova Neuroscience Center

PUBBLICAZIONI SELEZIONATE

Zorzi, M, & Testolin, A. (2018). An emergentist perspective on the origin of number sense. Phil. Trans. R. Soc. B, 373, 20170043.

Testolin, A., Stoianov, I., & Zorzi, M. (2017). Letter perception emerges from unsupervised learning and recycling of natural image features. Nature Human Behaviour, 1, 657–664.

Sella, F., Berteletti, I., Lucangeli, D., & Zorzi, M. (2017). Preschool children use space, rather than counting, to infer the numerical magnitude of digits: Evidence for a spatial mapping principle. Cognition, 158, 56-67.

Blini, E., Romeo, Z., Spironelli, C., Pitteri, M., Meneghello, F., Bonato, M., & Zorzi, M. (2016). Multi-tasking uncovers right spatial neglect and extinction in chronic left-hemisphere stroke patients. Neuropsychologia, 92, 147-157.

Sella, F., Berteletti, I., Lucangeli, D., & ZORZI, M. (2016). Spontaneous non-verbal counting in toddlers. Developmental Science, 19, 329-337.

Testolin, A., Stoianov, I., Sperduti, A., & Zorzi, M. (2016). Learning orthographic structure with sequential generative neural networks. Cognitive Science, 40, 579–606.

Lisi, M., Bonato, M., & Zorzi, M. (2015). Pupil dilation reveals top-down attentional load during spatial monitoring. Biological Psychology, 112, 39–45.

Cutini, S., Scarpa, F., Scatturin, P., Dell’Acqua, R. & Zorzi, M. (2014). Number-space interactions in the human parietal cortex: Enlightening the SNARC effect with functional Near-Infrared Spectroscopy. Cerebral Cortex, 24(2), 444-451.

Ziegler, JC., Perry, C., & Zorzi M. (2014). Modelling reading development through phonological decoding and self-teaching: implications for dyslexia. Philosophical Transactions of the Royal Society B: Biological Sciences, 369(1634), 20120397.

Zorzi, M., Barbiero, C., Facoetti, A., Lonciari, I., Carrozzi, M., Montico, M., Bravar, L., et al. (2012). Extra-large letter spacing improves reading in dyslexia. Proceedings of the National Academy of Sciences of the United States of America, 109(28), 11455-9.

Stoianov, I., & Zorzi, M. (2012). Emergence of a “visual number sense” in hierarchical generative models. Nature neuroscience, 15(2), 194-6.

Casarotti, M., Lisi, M., Umiltà, C., & Zorzi, M. (2012). Paying attention throgh eye movements: A computational investigation of the premotor theory of spatial attention. Journal of Cognitive Neuroscience, 14, 1519-1531.

Piazza, M., Facoetti, A., Trussardi, A. N., Berteletti, I., Conte, S., Lucangeli, D., Dehaene, S., & Zorzi, M. (2010). Developmental trajectory of number acuity reveals a severe impairment in developmental dyscalculia. Cognition, 116(1), 33-41.

Bonato, M., Priftis, K., Marenzi, R., Umiltà, C., & Zorzi, M. (2010). Increased attentional demands impair contralesional space awareness following stroke. Neuropsychologia, 48, 3934-3940.

Perry, C., Ziegler, J.C., & Zorzi, M. (2007). Nested incremental modeling in the development of computational theories: The CDP+ model of reading aloud. Psychological Review, 114, 273-315.

Zorzi M., Priftis, K., & Umilta` C. (2002). Neglect disrupts the mental number line. Nature, 417,138-139.

Le ricerche nel mio laboratorio sono rivolte allo studio delle basi neuro-computazionali delle funzioni cognitive nella normalità e nella patologia. Metodi: simulazione con modelli computazionali, neuropsicologia, neuroimmagine funzionale, psicologia sperimentale. Principali temi: 1) cognizione numerica e discalculia; 2) attenzione, rappresentazione dello spazio, neglect; 3) lettura e dislessia; 4) reti neurali (deep learning) e neuroscienze computazionali. Per maggiori informazioni consultare il sito web del Computational Cognitive Neuroscience Lab (http://ccnl.psy.unipd.it)

Research in my laboratory (Computational Cognitive Neuroscience Lab, http://ccnl.psy.unipd.it) is focused on the study of the computational bases of cognition, from development to skilled performance and to breakdowns of processing in atypical development or after brain damage. To address these issues we use a cognitive neuroscience approach that combines several methodologies, including computational modeling, behavioral studies (reaction times and psychophysics), neuropsychology, and functional neuroimaging (fMRI, fNIRS, EEG). Main themes: 1) numerical cognition and dyscalculia; 2) attention, space coding, neglect; 3) reading and dyslexia; 4) neural networks (deep learning) and computational neuroscience.

Argomenti di tesi:
- Intelligenza artificiale (reti neurali artificiali, deep learning, machine learning)
- Cognizione numerica (percezione della numerosità, spazio e numeri, discalculia)
- Attenzione spaziale (attenzione e cognizione, multitasking, neuropsicologia dell'attenzione)
- Processi di lettura (riconoscimento di parole, dislessia)
- Neuroimaging computazionale (connettomica, relazione cervello-comportamento)

Metodologie:
- Psicologia Sperimentale/Cognitiva
- Modellistica computazionale (solo Laurea Magistrale o Dottorato)
- Neuropsicologia (cerebrolesione o disturbi dell'apprendimento) (solo Laurea Magistrale o Dottorato)
- Neuroimmagine (fMRI, EEG, fNIRS) (solo Laurea Magistrale o Dottorato)

Per maggiori informazioni consultare il sito web del laboratorio:
Computational Cognitive Neuroscience Lab (http://ccnl.psy.unipd.it)

Supervisione tesi di dottorato: consultare la voce "Avvisi e altre informazioni"