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)
Random walks and diffusion on networks
Physics Reports (15 October 2017)
Backtracking and mixing rate of diffusion on uncorrelated temporal networks
Entropy issue 10 volume 19 (1 October 2017)
Multiscale mixing patterns in networks
arXiv (3 August 2017) Full text available
Graph spectral characterization of the XY model on complex networks
Physical Review E issue 1 volume 96 (11 July 2017)
Stationarity of the inter-event power-law distributions.
PloS one issue 3 volume 12 page e0174509-e0174509 (27 March 2017)
Complex systems - Dynamics on networks - Temporal networks
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.