The NEtwoRks, Data, and Society (NERDS) group, founded in 2019, is researching network and data science applications to social systems at ITU Copenhagen. NERDS consists of interdisciplinary researchers who focus on quantitative projects at the boundary of network science, data science, and computational social science, including science of science, social networks and dynamics, multiplex networks, science of success, urban sustainability, human mobility, data visualization, and fundamental questions in complex systems. We are Research Environment of the Year 2022.

Our research: https://pure.itu.dk/portal/en/organisations/networks-data-and-society/publications/


Email: luai@itu.dk
Office: 3F11 (DR P4), Kaj Munks Vej 9, 2300 København
IT University of Copenhagen, Rued Langgaards Vej 7, 2300 København

Mastodon: https://datasci.social/@nerdsitu
Github: https://github.com/NERDSITU

Our network, expertise, and funders

Our team brings data/network science expertise from institutions such as: MIT, Harvard, United Nations, Nokia Bell Labs, Northeastern University

We are well connected on an international level to, for example: MIT, Harvard, United Nations, Northeastern University, University of Chicago, ISI Foundation, Complexity Science Hub Vienna
We are well connected on a national level to, for example: DTU, KU (SODAS), Aarhus University, Dansk Kyst- og Naturturisme

Our funders include: VILLUM Foundation, Carlsberg Foundation, Danish Ministry of Transport, European Commission, CHANSE, Innovation Fund Denmark


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Foundational NERDS research

Our most important, defining works are:

R. Sinatra, D. Wang, P. Deville, C. Song, and A.-L. Barabási
Quantifying the evolution of individual scientific impact
Science, 354, 6312 (2016)

V. Sekara, A. Stopczynski, S. Lehmann
Fundamental structures of dynamic social networks
Proceedings of the National Academy of Sciences, USA 113 (36), 9977-9982 (2016)

LM Aiello et al.
Sensing trending topics in Twitter
IEEE Transactions on Multimedia 15 (6), 1268-1282 (2013)

M. Coscia, G. Rossetti, F. Giannotti, D. Pedreschi
Demon: a local-first discovery method for overlapping communities
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining (2012)

M. Magnani, L. Rossi
The ml-model for multi-layer social networks
IEEE, Proceeding of 2011 International Conference on Advances in Social Networks Analysis and Mining (2011)

M. Szell, R. Lambiotte, S. Thurner
Multirelational organization of large-scale social networks in an online world
Proceedings of the National Academy of Sciences USA 107(31), 13636-13641 (2010)