Simone Daniotti has been a PhD candidate at the Complexity Science Hub since October 2021.
He received his master’s degree in physics at the University of Studies of Milano with a thesis in collaboration with Sony Computer Science Laboratories Paris entitled “Maximum Entropy Approach for the prediction of Urban Mobility Patterns”. In this work, Simone studied the activity and the correlations between different zones of a metropolitan area, using statistical inference and machine learning models.
Simone is also pursuing his PhD at TU Wien.
Currently, Simone’s research interest lies in the crossing point of social science and mathematics. His primary areas of focus revolve around mobility, public transportation, and the economic aspects of urban environments. He employs various methodologies, including complex network analysis, statistical methods, and agent-based simulations, to explore and understand these topics.
The machine learning model that can predict a city’s traffic [feat. Simone Daniotti]
Engineers Ireland, Mar 13, 2023
Jak przewidzieć natężenie ruchu w mieście [polish] [feat. Simone Daniotti]
Wirtualne Media, Mar 6, 2023