Associate Professor of Networks and Nonlinear Systems
+44 1865 280608
University of Oxford
Andrew Wiles Building
Radcliffe Observatory Quarter
A Guide to Temporal Networks
ISBN-13: 9781786341167 (28 July 2016)
Diffusion on networked systems is a question of time or structure.
Nature communications volume 6 page 7366-7366 (9 June 2017)
The many facets of community detection in complex networks
Schaub, M.T., Delvenne, JC., Rosvall, M. et al. Appl Netw Sci (2017) 2: 4 (3 February 2017) Full text available
Random Walks, Markov Processes and the Multiscale Modular Organization
of Complex Networks
IEEE Transactions on Network Science and Engineering (Volume:1 , Issue: 2 ) pp 76-90, 2015 (2 January 2015) Full text available
Memory in network flows and its effects on spreading dynamics and community detection.
Nature Communications volume 5 page 4630-4630 (11 August 2014)
Multirelational organization of large-scale social networks in an online world.
Proceedings of the National Academy of Sciences of the United States of America issue 31 volume 107 page 13636-13641 (1 August 2010)
ISBN-13: 9783030054137 (1 January 2019)
Structure and dynamical behavior of non-normal networks.
Science advances issue 12 volume 4 page eaau9403- (12 December 2018)
Random walk on temporal networks with lasting edges
Physical Review E (20 November 2018) Full text available
Identifying exogenous and endogenous activity in social media
Physical Review E (13 November 2018) Full text available
Complex systems - Dynamics on networks - Temporal networks
Mathematical Institute, Andrew Wiles Building, University of Oxford, Radcliffe Observatory Quarter, Woodstock Rd, Oxford OX2 6GG, UK
Renaud Lambiotte has a PhD in physics from the Université libre de Bruxelles. After postdocs at ENS Lyon, Université de Liège, UCLouvain and Imperial College London, and a professorship in Mathematics at the University of Namur, he is currently associate professor at the Mathematical Institute of Oxford University. His main research interests are the modelling and analysis of processes taking place on large networks, with a particular focus on social and brain networks.