List of Publications

I have published 76 articles/preprints 2020 Quantifying the importance and location of SARS-CoV-2 transmission events in large metropolitan areas Alberto Aleta, David Martin-Corral, Michiel A. Bakker, Ana Pastore y Piontti, Marco Ajelli, Maria Litvinova, Matteo Chinazzi, Natalie E. Dean, M. Elizabeth Halloran, Ira M. Longini, Alex Pentland, Alessandro Vespignani, Yamir Moreno, Esteban Moro Preprint (2020) PDF medXiv Altmetric: 264 Leveraging Communication Topologies Between Learning Agents in Deep Reinforcement Learning ...

#covid19 #super-spreading #Mobile phone data

Quantifying the importance and location of SARS-CoV-2 transmission events in large metropolitan areas

Authors: Alberto Aleta, David Martin-Corral, Michiel Bakker, Ana Pastore y Piontti, Marco Ajelli, Maria Litvinova, Matteo Chinazzi, Natalie E Dean,M. Elizabeth Halloran, Ira M Longini, Alex Pentland, Alessandro Vespignani, Yamir Moreno, Esteban Moro Publication: medRxiv (2020). Link Abstract: Detailed characterizations of SARS-CoV-2 transmission risk across different social settings can inform the design of targeted and less disruptive non-pharmaceutical interventions (NPI), yet these data have been lacking. Here we integrate real-time, anonymous and privacy-enhanced geolocalized mobility data with census and demographic data in the New York City and Seattle metropolitan areas to build a detailed agent-based model of SARS-CoV-2 transmission. ...

#covid19 #Mobility #epidemics

Modeling the impact of social distancing, testing, contact tracing and household quarantine on second-wave scenarios of the COVID-19 epidemic

Authors: Alberto Aleta, David Martíın-Corral, Ana Pastore y Piontti, Marco Ajelli, Maria Litvinova, Matteo Chinazzi, Natalie E. Dean, M. Elizabeth Halloran, Ira M. Longini, Jr., Stefano Merler, Alex Pentland, Alessandro Vespignani, Esteban Moro & Yamir Moreno Publication: Nature Human Behavior(2020). Link Abstract: While severe social-distancing measures have proven effective in slowing the coronavirus disease 2019 (COVID-19) pandemic, second-wave scenarios are likely to emerge as restrictions are lifted. Here we integrate anonymized, geolocalized mobility data with census and demographic data to build a detailed agent-based model of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission in the Boston metropolitan area. ...

#Privacy #Social Networks #Prediction algorithms

How to Hide One's Relationships from Link Prediction Algorithms

Authors: Marcin Waniek, Kai Zhou, Yevgeniy Vorobeychik, Esteban Moro, Tomasz P Michalak, Talal Rahwan Journal: Scientific Reports volume 9, Article number: 12208 (2019) Link Abstract: Our private connections can be exposed by link prediction algorithms. To date, this threat has only been addressed from the perspective of a central authority, completely neglecting the possibility that members of the social network can themselves mitigate such threats. We fill this gap by studying how an individual can rewire her own network neighborhood to hide her sensitive relationships. ...

#Artificial Intelligence #Labour Markets

Towards understanding the impact of artificial intelligence on labor

Authors: Frank, Morgan R and Autor, David and Bessen, James E and Brynjolfsson, Erik and Cebrian, Manuel and Deming, David J and Feldman, Maryann and Groh, Matthew and Lobo, José and Moro, Esteban and Wang, Dashun and Youn, Hyejin and Rahwan, Iyad Journal: PNAS (2019). JOURNAL | PDF Abstract: Rapid advances in artificial intelligence (AI) and automation technologies have the potential to significantly disrupt labor markets. While AI and automation can augment the productivity of some workers, they can replace the work done by others and will likely transform almost all occupations at least to some degree. ...

#Deep Learning #Networks

How to Organize your Deep Reinforcement Learning Agents: The Importance of Communication Topology

Authors: Dhaval Adjodah, Dan Calacci, Abhimanyu Dubey, Peter Krafft, Esteban Moro, Alex `Sandy’ Pentland Journal: Preprint (2018). arXiv Abstract: In this empirical paper, we investigate how learning agents can be arranged in more efficient communication topologies for improved learning. This is an important problem because a common technique to improve speed and robustness of learning in deep reinforcement learning and many other machine learning algorithms is to run multiple learning agents in parallel. ...