Charlton, N., Singleton, C. and Greetham, D. V. (2016) In the mood: the dynamics of collective sentiments on Twitter. Royal Society Open Science, 3 (6). 160162. ISSN 2054-5703 doi: https://doi.org/10.1098/rsos.160162

Charlton, N., Vukadinovic Greetham, D. and Singleton, C. (2013) Graph-based algorithms for comparison and prediction of household-level energy use profiles. In: IEEE International Workshop on Intelligent Energy Systems, 14 Nov 2013, Wienna, pp. 119-124.

Colman, E. and Vukadinovic Greetham, D. (2015) Memory and burstiness in dynamic networks. Physical Review E, 92 (1). 012817. ISSN 1539-3755 doi: https://doi.org/10.1103/PhysRevE.92.012817

Della Giusta, M. ORCID: https://orcid.org/0000-0003-3959-4451, Jaworska, S. ORCID: https://orcid.org/0000-0001-7465-2245 and Vukadinovic Greetham, D. (2021) Expert communication on Twitter: comparing economists and scientists’ social networks, topics and communicative styles. Public Understanding of Science, 30 (1). pp. 75-90. ISSN 1361-6609 doi: https://doi.org/10.1177/0963662520957252

Erlebach, T., Moonen, L., Spieksma, F. and Vukadinovic Greetham, D. (2009) Connectivity measures for internet topologies on the level of autonomous systems. Operations Research, 57 (4). pp. 1006-1025. ISSN 1526-5463 doi: https://doi.org/10.1287/opre.1080.0677

Giasemidis, G. and Vukadinovic Greetham, D. (2018) Optimising parameters in recurrence quantification analysis of smart energy systems. In: 9th International Conference on Information, Intelligence, Systems and Applications (IISA2018), 23-25 July 2015, Zakynthos, Greece.

Giasemidis, G., Singleton, C., Agrafiotis, I., Nurse, J. R. C., Pilgrim, A., Willis, C. and Vukadinovic Greetham, D. (2016) Determining the veracity of rumours on Twitter. In: 8th International Conference on Social Informatics, SocInfo 2016, 15-17 November 2016, Seattle, USA, pp. 185-205.

Giasemidis, G. and Haben, S. (2018) Modelling the demand and uncertainty of low voltage networks and the effect of non-domestic consumers. Sustainable Energy, Grids and Networks, 16. pp. 341-340. ISSN 2352-4677 doi: https://doi.org/10.1016/j.segan.2018.10.002

Giasemidis, G., Haben, S., Lee, T., Singleton, C. and Grindrod, P. (2017) A genetic algorithm approach for modelling low voltage network demands. Applied Energy, 203 (1). pp. 463-473. ISSN 0306-2619 doi: https://doi.org/10.1016/j.apenergy.2017.06.057

Giasemidis, G., Kaplis, N., Agrafiotis, I. and Nurce, J. R. C. (2020) A semi-supervised approach to message stance classification. IEEE Transactions on Knowledge and Data Engineering, 32 (1). pp. 1-11. ISSN 1041-4347 doi: https://doi.org/10.1109/TKDE.2018.2880192

Grindrod, P. (2015) Evolving social networks, attitudes and beliefs and counter terrorism. In: Higham, N. J. (ed.) The Princeton companion to applied mathematics. Princeton University Press, Princeton, N.J., pp. 800-803. ISBN 9780691150390 (Part VII.5 )

Grindrod, P. (2011) Mathematical modelling for the digital society. IMA Journal of Applied Mathematics, 76 (3). pp. 475-492. ISSN 1464-3634 doi: https://doi.org/10.1093/imamat/hxq050

Grindrod, P. and Higham, D. J. (2010) Evolving graphs: dynamical models, inverse problems and propagation. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 466 (2115). pp. 753-770. ISSN 1364-5021 doi: https://doi.org/10.1098/rspa.2009.0456

Grindrod, P. and Higham, D. J. (2012) Models for evolving networks: with applications in telecommunication and online activities. IMA Journal of Management Mathematics, 23 (1). pp. 1-15. ISSN 1471-6798 doi: https://doi.org/10.1093/imaman/dpr001

Grindrod, P. and Higham, D. J. (2012) A matrix iteration for dynamic network summaries. SIAM Review, 55 (1). pp. 118-128. ISSN 1095-7200 doi: https://doi.org/10.1137/110855715

Grindrod, P. and Parsons, M. (2011) Social networks: evolving graphs with memory dependent edges. Physica A, 390 (2. pp. 3970-3981. doi: https://doi.org/10.1016/j.physa.2011.06.015

Grindrod, P. and Pinotsis, D. (2010) On the spectra of certain integro-differential-delay problems with applications in neurodynamics. Physica D: Nonlinear Phenomena, 240 (1). pp. 13-20. ISSN 0167-2789 doi: https://doi.org/10.1016/j.physd.2010.08.002

Grindrod, P., Higham, D. J. and Kalna, G. (2010) Periodic Reordering. IMA Journal of Numerical Analysis, 30 (1). pp. 195-207. ISSN 0272-4979 doi: https://doi.org/10.1093/imanum/drp047

Grindrod, P., Higham, D. J. and Parsons, M. C. (2012) Bistability through triadic closure. Internet Mathematics, 8 (4). pp. 402-423. doi: https://doi.org/10.1080/15427951.2012.714718

Grindrod, P., Parsons, M. C., Higham, D. J. and Estrada, E. (2011) Communicability across evolving networks. Physical Review E, 83 (4). 046120. ISSN 1539-3755 doi: https://doi.org/10.1103/PhysRevE.83.046120

Grindrod, P., Stoyanov, Z. V., Smith, G. M. and Saddy, J. D. ORCID: https://orcid.org/0000-0001-8501-6076 (2013) Primary evolving networks and the comparative analysis of robust and fragile structures. Journal of Complex Networks, 2 (1). pp. 60-73. ISSN 2051-1329 doi: https://doi.org/10.1093/comnet/cnt015

Haben, S. and Giasemidis, G. (2018) Distribution network demand and its uncertainty. In: Arefi, A., Shahnia, F. and Ledwich, G. (eds.) Electric Distribution Network Management and Control. Springer, pp. 59-84. ISBN 9789811070013 doi: https://doi.org/10.1007/978-981-10-7001-3_3

Haben, S., Singleton, C. and Grindrod, P. (2016) Analysis and clustering of residential customers energy behavioral demand using smart meter data. IEEE Transactions on Smart Grid, 7 (1). pp. 136-144. ISSN 1949-3053 doi: https://doi.org/10.1109/TSG.2015.2409786

Haben, S., Ward, J., Vukadinovic Greetham, D., Singleton, C. and Grindrod, P. (2014) A new error measure for forecasts of household-level, high resolution electrical energy consumption. International Journal of Forecasting, 30 (2). pp. 246-256. ISSN 0169-2070 doi: https://doi.org/10.1016/j.ijforecast.2013.08.002

Haben, S. and Giasemidis, G. (2016) A hybrid model of kernel density estimation and quantile regression for GEFCom2014 probabilistic load forecasting. International Journal of Forecasting, 32 (3). pp. 1017-1022. ISSN 0169-2070 doi: https://doi.org/10.1016/j.ijforecast.2015.11.004

Hattam, L., Vukadinovic Greetham, D., Haben, S. and Roberts, D. (2017) Electric vehicles and low voltage grid: impact of uncontrolled demand side response. In: 24th International Conference on Electricity Distribution, 12-15 June 2017, Glasgow, pp. 1073-1076.

Hattam, L. (2018) Travelling wave solutions of the perturbed mKdV equation that represent traffic congestion. Wave Motion, 79. pp. 57-72. ISSN 0165-2125 doi: https://doi.org/10.1016/j.wavemoti.2018.02.006

Hattam, L. and Vukadinovic Greetham, D. (2018) Energy disaggregation for SMEs using recurrence quantification analysis. In: ACM e-Energy 2018, 12 Jun 2018, Karlsruhe, Germany, pp. 610-617.

Hattam, L. and Vukadinovic Greetham, D. (2017) Green neighbourhoods in low voltage networks: measuring impact of electric vehicles and photovoltaics on load profiles. Journal of Modern Power Systems and Clean Energy, 5 (1). pp. 105-116. ISSN 2196-5420 doi: https://doi.org/10.1007/s40565-016-0253-0

Hattam, L. and Vukadinovic Greetham, D. (2018) An innovation diffusion model of a local electricity network that is influenced by internal and external factors. Physica A: Statistical Mechanics and its Applications, 490. pp. 353-365. ISSN 0378-4371 doi: https://doi.org/10.1016/j.physa.2017.08.014

Hattam, L. L. (2017) KdV cnoidal waves in a traffic flow model with periodic boundaries. Physica D: Nonlinear Phenomena, 348. pp. 44-53. ISSN 0167-2789 doi: https://doi.org/10.1016/j.physd.2017.02.010

Higham, D. J., Batty, M., Bettencourt, L. M., Greetham, D. V. and Grindrod, P. (2017) An overview of City Analytics. Royal Society Open Science, 4 (2). 161063. ISSN 2054-5703 doi: https://doi.org/10.1098/rsos.161063

Ngoh, S., Pal Majumder, A. ORCID: https://orcid.org/0000-0001-6094-4909 and Lingjie, D. (2024) Robust clustered federated learning against malicious agents. In: 2024 IEEE 99th Vehicular Technology Conference (VTC2024-Spring), June 24−June 27th , 2024, Singapore. (In Press)

Parsons, M. C. and Grindrod, P. (2012) Competing edge networks. Physics Letters A, 376 (32). pp. 2167-2173. ISSN 0375-9601 doi: https://doi.org/10.1016/j.physleta.2012.05.008

Poghosyan, A., Vukadinovic Greetham, D., Haben, S. and Lee, T. (2015) Long term individual load forecast under different electrical vehicles uptake scenarios. Applied Energy, 157. pp. 699-709. ISSN 0306-2619 doi: https://doi.org/10.1016/j.apenergy.2015.02.069

Richetin, J., Perugini, M., Connor, M., Adjali, I., Hurling , R., Sengupta, A. and Greetham, D. (2012) To reduce and not to reduce resource consumption? That is two questions. Journal for Environmental Psychology, 33 (2). pp. 112-122. ISSN 0272-4944 doi: https://doi.org/10.1016/j.jenvp.2012.01.003

Richetin, J., Sengupta, A., Perugini, M., Adjali, I., Hurling, R., Vukadinovic Greetham, D. and Spence , M. (2010) A micro-level simulation for the prediction of intention and behaviour. Cognitive Systems Research, 11 (2). pp. 181-193. ISSN 1389-0417 doi: https://doi.org/10.1016/j.cogsys.2009.08.001

Sengupta, A. and Greetham, D. V. (2010) Dynamics of brand competition: Effects of unobserved social networks. Journal of Economic Dynamics and Control, 34 (12). pp. 2391-2406. ISSN 0165-1889 doi: https://doi.org/10.1016/j.jedc.2010.06.009

Singleton, C. and Charlton, N. (2014) A refined parametric model for short term load forecasting. International Journal of Forecasting, 30 (2). 364 - 368. ISSN 0169-2070 doi: https://doi.org/10.1016/j.ijforecast.2013.07.003

Smith, G., Stoyanov, Z., Vukadinovic Greetham, D., Grindrod, P. and Saddy, D. ORCID: https://orcid.org/0000-0001-8501-6076 (2014) Towards the computer-aided diagnosis of dementia based on the geometric and network connectivity of structural MRI data. In: CADDementia workshop, Medical Image Computing and Computer Assisted Intervention (MICCAI) 2014 conference, 14-18 Sep 2014, Boston.

Vukadinovic Greetham, D. and Ward, J. A. (2014) Conversations on Twitter: structure, pace, balance. In: 2nd International Workshop on Dynamic Networks and Knowledge Discovery (DyNaK II), 15 September 2014, Nancy, France. (ISSN 1613-0073)

Vukadinovic Greetham, D., Poghosyan, A. and Charlton, N. (2015) Weighted alpha-rate dominating sets in social networks. In: Third International Workshop on Complex Networks and their Applications, 23-27 Nov 2014, Marrakech, Morocco.

Vukadinovic Greetham, D., Stoyanov, Z. and Grindrod, P. (2013) Centrality and spectral radius in dynamic communication networks. In: CSoNet, COCOON 2013, LNCS 7936, 22 June 2013, Hangzhou, China, pp. 791-800.

Vukadinovic Greetham, D., Hurling, R., Osborne, G. and Linley, A. (2011) Social networks and positive and negative affect. Procedia Social and Behavioural Sciences, 22. pp. 4-13. ISSN 1877-0428 doi: https://doi.org/10.1016/j.sbspro.2011.07.051

Vukadinovic Greetham, D., Sengupta, A., Hurling, R. and Wilkinson, J. (2015) Interventions in social networks: impact on mood and network dynamics. Advances in Complex Systems, 18 (03n04). p. 1550016. ISSN 1793-6802 doi: https://doi.org/10.1142/S0219525915500162

Vukadinovic Greetham, D., Stoyanov, Z. and Grindrod, P. (2014) On the radius of centrality in evolving communication networks. Journal of Combinatorial Optimization, 28 (3). pp. 540-560. ISSN 1382-6905 doi: https://doi.org/10.1007/s10878-014-9726-0

Yunusov, T. ORCID: https://orcid.org/0000-0003-2318-3009, Giasemidis, G. and Haben, S. (2018) Smart storage scheduling and forecasting for peak reduction on low-voltage feeders. In: Energy Management—Collective and Computational Intelligence with Theory and Applications. Studies in Systems, Decision and Control, 149. Springer, pp. 83-107. ISBN 9783319756905 doi: https://doi.org/10.1007/978-3-319-75690-5_5

Yunusov, T. ORCID: https://orcid.org/0000-0003-2318-3009, Haben, S., Lee, T., Ziel, F., Holderbaum, W. and Potter, B. (2017) Evaluating the effectiveness of storage control in reducing peak demand on low voltage feeders. In: CIRED 2017, 12-15 Jun 2017, Glasgow, UK, pp. 1745-1749.