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Bernardo Monechi PhD

Bernardo Monechi PhD

Sony Computer Science Laboratories Paris

Cities are the social and economic innovation core of modern nations. Despite their importance, they still suffer from many problems: social segregation, accessibility inequality, overcrowding, pollution and infrastructure malfunctions are only a few examples. In my research, I exploit the specific tools of Complex Systems Physics and Machine Learning to find new approaches for studying Urban Environments, looking for solutions to their sustainability problems. I am also interested in general techno-social systems’ modelisation (Music Production, Railway Systems, Innovation Dynamics), involving citizens in the research process through their engagement in gamified social experiments.

Experimental Settings for studying Creativity and Learning in Museums

In this talk, I will discuss some of my recent works connected with social experiments about the study of collective creativity and learning about urban sustainability. In the first part, I will show the results coming from an experiment realized some years ago, during the Kreyon Days open event in PalaExpo in Rome. During this event, visitors could take part in an open-ended experiment, where they were asked to build some LEGO artworks collectively. RFID sensors, given to the participants, allowed for the reconstruction of the dynamical social network and the identification of teams that were contributing to a specific artwork. This data allowed for the identification of some of the characteristics of the most efficient building teams. For those interested, the work can be found here: https://www.pnas.org/content/116/44/22088 In the second part, I will discuss an ongoing experiment that is taking place during the “AI: More than human exhibition” in London and Groeningen. This experiment, dubbed “Kreyon City,” aims at understanding how individuals relate to complex sustainability problems. I will discuss the experience and some preliminary results coming from the analysis of the first tranche of collected data.