Dr Nicola Perra

Profile

Nicola is a Reader in Applied Mathematics at the School of Mathematical Science. His research focuses on human dynamics, data analytics, network science, mathematical and digital epidemiology.

After completing his PhD in theoretical physics at the University of Cagliari (Italy), he held various positions at Indiana University, Northeastern University, and Greenwich University. 

For Nicola's personal webpage, please visit http://www.nicolaperra.com/

Research

Research Interests:

See Nicola Perra’s research profile pages including details of research interests, publications, and live grants.

Publications

• Gozzi N, Chinazzi M, Davis JT et al. (2024). Real-time Estimates of the Emergence and Dynamics of SARS-CoV-2 Variants of Concern: A Modeling Approach Epidemics: The Journal on Infectious Disease Dynamics .

  10.1016/j.epidem.2024.100805

  https://qmro.qmul.ac.uk/xmlui/handle/123456789/102085
• Gozzi N, Comini N, Perra N . Bridging the digital divide: mapping Internet connectivity evolution, inequalities, and resilience in six Brazilian cities EPJ Data Science .

  10.1140/epjds/s13688-024-00508-8

  https://qmro.qmul.ac.uk/xmlui/handle/123456789/102362
• Manna A, D'Amico L, Tizzoni M et al. (2024). Generalized Contact Matrices Allow Integrating Socio-economic Variables into Epidemic Models Science Advances .

  10.1126/sciadv.adk4606

  https://qmro.qmul.ac.uk/xmlui/handle/123456789/99436
• Gozzi N, Comini N, Perra N (2024). Bridging the Digital Divide: Mapping Internet Connectivity Evolution, Inequalities, and Resilience in six Brazilian Cities .

  10.48550/arxiv.2406.01113

  https://qmro.qmul.ac.uk/xmlui/handle/123456789/101235
• Chinazzi M, Davis JT, Y Piontti AP et al. (2024). A multiscale modeling framework for Scenario Modeling: Characterizing the heterogeneity of the COVID-19 epidemic in the US Epidemics .

  10.1016/j.epidem.2024.100757

  https://qmro.qmul.ac.uk/xmlui/handle/123456789/95145
• Carli F, Foini P, Gozzi N et al. . Modeling teams performance using deep representational learning on graphs EPJ Data Science .

  10.1140/epjds/s13688-023-00442-1

  https://qmro.qmul.ac.uk/xmlui/handle/123456789/94163
• Gao S, Dai X, Wang L et al. (2023). Epidemic Spreading in Metapopulation Networks Coupled With Awareness Propagation IEEE Transactions on Cybernetics .

  10.1109/tcyb.2022.3198732

  https://uat2-qmro.qmul.ac.uk/xmlui/handle/123456789/80498
• Sun K, Ubaldi E, Zhang J et al. (2023). The Effects of Local and Global Link Creation Mechanisms on Contagion Processes Unfolding on Time-Varying Networks .

  10.1007/978-3-031-30399-9_16
• De Gaetano A, Bajardi P, Gozzi N et al. . Behavioral Changes Associated With COVID-19 Vaccination: Cross-National Online Survey Journal of Medical Internet Research .

  10.2196/47563

  https://qmro.qmul.ac.uk/xmlui/handle/123456789/91420
• Jaramillo AM, Williams HTP, Perra N et al. . The structure of segregation in co-authorship networks and its impact on scientific production EPJ Data Science .

  10.1140/epjds/s13688-023-00411-8

  https://qmro.qmul.ac.uk/xmlui/handle/123456789/90811