Dzięki uprzejmości Wydziału Psychologii UW już w tym tygodniu mamy zaszczyt gościć prof. Marco Zorzi z Uniwerytetu Padewskiego. Wygłosi on miniserię wykładów otwartych:
From pixels to numbers: Numerosity perception in humans and machines – wykład odbędzie się w środę 21.05.2025 o godzinie 17:00 w sali 0.06 na Wydziale Fizyki Uniwersytetu Warszawskiego.
Abstact: How is visual numerosity computed from images? How is numerical information encoded and how it relates to non-numerical visual magnitudes? Why does numerosity discrimination improve during development but it lags behind in dyscalculia? This talk will address these issues using computational simulations with deep neural networks.
Computational modelling of cognition: methods and challenges – wykład odbędzie się w czwartek 22.05.2025 o godzinie 17:30 w sali 0.06 na Wydziale Fizyki Uniwersytetu Warszawskiego.
Abstact: The lecture will cover basic methodological issues in computational modeling of cognition. Starting from a taxonomy of cognitive models and the aims of computational modeling, the discussion will focus on evaluation criteria and their application to connectionist (neural network) models.
Marco Zorzi is Full Professor of Artificial Intelligence and Cognitive Psychology at the University of Padova, and Senior Researcher at IRCCS San Camillo Neurorehabilitation Hospital in Venice-Lido.
Trained in cognitive psychology, computational modelling, computational and cognitive neuroscience during doctoral and postdoctoral studies in Trieste (University of Trieste and SISSA), London (UCL) and Padova, he joined San Raffaele University-Milan in 2000 as assistant professor and the University of Padova in 2001 as associate professor (full professor since 2006).
In 2001 he set up the Computational Cognitive Neuroscience Lab, an interdisciplinary research laboratory at the frontiers between cognitive science, computer science and neuroscience, focused on the computational bases of human cognition. Computational modeling based on artificial neural networks is complemented by empirical studies on adults (both healthy and neurologically impaired) and children (both typically and atypically developing) using behavioral and cognitive neuroscience methods.
Recent computational work was supported by the European Research Council and exploits deep learning and probabilistic graphical models to produce realistic simulations of human neurocognitive functions. State-of-the-art machine learning methods are also applied to neuroinformatics (neuroimaging data) and industrial applications.
Major past grants include Italian Ministry of Education and University (PRIN 2002, 2004, 2006, 2008), Italian Ministry of Health (RF 2013), University of Padova (Strategic Grants), Cariparo Foundation (Excellence Grants), Compagnia di San Paolo (Neuroscience Program), European Commission (FP5 and FP6, Marie Curie RTN), European Research Council.
