I'm an Associate Professor in Mathematics at City, University of London and the Economic Data Science theme lead at The Alan Turing Institute, where I created the Token Economy group. I am also Research Associate at the UCL Centre for Blockchain Technologies.
A physicist by training, my work focuses on the quantitative understanding of human individual and collective behaviour. In particular I am interested in how we shape, and are shaped by, the socio-technical systems we inhabit. I have helped advance our understanding on such topics as:
Coordination and spreading phenomena on social networks: norms, information / behaviour / opinion reading, infodemics, and category systems;
Collective behaviour change: tipping points, norm change, cultural evolution;
Blockchain & cryptocurrencies: market, development, usage and governance of cryptos and NFTs;
Online marketplaces: online & dark web marketplaces;
Human mobility, and
Fundamental problems in network science: temporal networks, random walks, diffusion processes, etc.
My interdisciplinary approach is primarily informed by concepts and tools from the physics of complex systems, network science and data science, and I collaborate with colleagues in social, economic and cognitive sciences. My methodology includes the analysis of large amount of data, mathematical modelling, and lab experiments with human subjects.
My research has appeared in a wide range of journals including Science, PNAS, Nature Human Behaviour, Science Advances, Nature Communications, Physical Review Letters and Trends in Cognitive Science. It has been extensively covered by the media (NYT, The Economist, Washington Post, BBC, Le Monde, La Repubblica, Scientific American, MIT Tech Review, etc), and supported by public and private bodies (UKRI, ESRC, InnovateUK, UK Govt., etc). My work was recognised by the 2019 Young Scientist Award for Socio and Econophysics awarded by the German Physical Society.
Besides academia, I regularly help start-ups and companies in the blockchain/crypto space improve their products by assessing, and anticipating, the behaviour of the communities they aim to reach.
How norms change
IC2S2'20 Keynote talk
Collective Dynamics of Dark Web Marketplaces
ACM Collective Intelligence '20
From code to market: Network of developers and correlated returns of cryptocurrencies. Lucchini, Alessandretti, Lepri, Gallo and Baronchelli Science Advances (2020)
The dynamics of norm change in the cultural evolution of language. Amato, Lacasa, Díaz-Guilera and Baronchelli PNAS (2018)
Experimental evidence for tipping points in social convention. Centola, Becker, Brackbill and Baronchelli Science (2018)
Evidence for a conserved quantity in human mobility. Alessandretti, Sapiezynski, Sekara, Lehmann and Baronchelli Nat. Hum. Behav. (2018)
Evolutionary dynamics of the cryptocurrency market. ElBahrawy, Alessandretti, Kandler, Pastor-Satorras, and Baronchelli RSOS (2017)
The spontaneous emergence of conventions: An experimental study of cultural evolution. Centola and Baronchelli PNAS (2015)
Modeling human dynamics of face-to-face interaction networks. Starnini, Baronchelli and Pastor-Satorras Phys. Rev. Lett. (2013)
Random Walks and Search in Time-Varying Networks. Perra, Baronchelli, Mocanu, Goncalves, Pastor-Satorras and Vespignani Phys. Rev. Lett. (2012)
Modeling the emergence of universality in color naming patterns. Baronchelli, Gong, Puglisi and Loreto PNAS (2010)
Cultural route to the emergence of linguistic categories. Puglisi, Baronchelli and Loreto PNAS (2008)
Sharp transition towards shared vocabularies in multi-agent systems. Baronchelli, Felici, Loreto, Caglioti and Steels J. Stat. Mech. P06014 (2006)