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Stefano Vrizzi


Support staff

29 rue d'Ulm
75005 Paris France

Human reinforcement learning
Stefano is interested in understanding the source of variability in people's responses to similar contexts. As his long-term goal, he aims to develop, discuss and test a filter-based framework to characterise information-processing in humans, in principle applicable also to other biological or artificial agents. He pursues his goal as curiosity-driven basic research as well as to promote awareness about how you and others think and perceive the world.
He is currently working as research assistant in the Human Reinforcement Learning Team with Stefano Palminteri to address individual variability in reinforcement learning.
Most of his theoretical and computational background comes from his master's degree in Neural Information Processing [1], his master thesis on information thermodynamics [2] and his undergraduate research fellowship in computational neuroscience [3]. Previously, he studied the physiological bases of information processing through his BSc in Neuroscience [4].
In order to study the consequences of decision-making on a collective scale, Stefano also pursued experience in the field of sustainability, especially eco-economic decoupling [5].
Finally, he has often been involved in organising events to encourage knowledge sharing and to connect concepts or people.

[1] Graduate Training Centre in Neuroscience, International Max Planck Research School, Eberhard Karls Universität Tübingen, Germany
[2] Quantitative Life Science, International Centre for Theoretical Physics, Trieste, Italy
[3] Fairhall lab, University of Washington Institute for Neuroengineering, Seattle, USA
[4] Faculty of Biological Sciences, University of Leeds, Leeds, UK
[5] Global Trends Unit, European Parliamentary Research Service, European Parliament, Brussels, Belgium