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Ramon Granell Senior researcher

Ramon Granell

Senior Researcher

Biography

Ramon Granell is a researcher at the Oxford e-Research Centre currently working as a knowledge engineer with Professor Susanna-Assunta Sansone in the area of data management for biomedical sciences.

He applies data analytic techniques to enrich data/publications repositories and platforms utilised under the FAIR (Findable, Accessible, Interoperable and Reusable) principle.

Ramon has been working at the Oxford e-Research Centre since 2010, investigating in different areas such as energy analytics and computational linguistics. Before that, he worked at Department of computer Science, University of Oxford. He holds a Computer Science degree and ML master from the Universidad Politecnica de Valencia (Spain).

ORCiD

Awards and Achievements

Granted research proposals

EPSRC Impact Acceleration Account. Modelling and prediction of the energy demand of stores using data-driven approaches. 2017-2018

Best poster exhibition prize

Granell, R.; Axon, C.J.; Kolokotroni, M.; Wallom, D.C.H.; "Does the London urban heat island affect electricity consumption of small supermarkets?" Manchester Energy and Electrical Power Systems "Big Data Applications in Power Systems" Workshop. Manchester (UK), 2017

Best poster award

Granell, R.; Axon, C.J.; Wallom, D.C.H.; "A Dirichlet process mixture model for clustering of household electricity load profiles". In: 9th International Conference on Machine Learning and Data Mining, Poster Proceedings, pp. 1-6 New York (USA), 2013.

Most Recent Publications

The FAIR Cookbook - the essential resource for and by FAIR doers.

The FAIR Cookbook - the essential resource for and by FAIR doers.

The FAIR Cookbook - the essential resource for and by FAIR doers.

The FAIR Cookbook - the essential resource for and by FAIR doers.

Predicting electricity demand profiles of new supermarkets using machine learning

Predicting electricity demand profiles of new supermarkets using machine learning

Helping the Consumers and Producers of Standards, Repositories and Policies to Enable FAIR Data

Helping the Consumers and Producers of Standards, Repositories and Policies to Enable FAIR Data

Implementation of a novel multi-agent system for demand response management in low-voltage distribution networks

Implementation of a novel multi-agent system for demand response management in low-voltage distribution networks

View all

Research Interests

Data analytics and machine learning techniques applied to different areas such as energy, linguistics and data management.

Projects

  • EPSRC Impact Acceleration Account  Modelling and prediction of the energy demand of stores using data-driven approaches. 2017-2018
  • Wordovators project (John Templeton Foundation)  2016-2017
  • EPSRC-funded WICKED project  (Working with Infrastructure Creation of Knowledge and Energy strategy Development) 2014-2016
  • EPSRC-funded ADEPT project  (Advanced Dynamic Energy Pricing and Tariffs). 2010-2014
  • EU-Funded Companions project  (Companions: Intelligent, Persistent, Personalised Multimodal Interfaces to the Internet). 2007-2010

Research Groups

Most Recent Publications

The FAIR Cookbook - the essential resource for and by FAIR doers.

The FAIR Cookbook - the essential resource for and by FAIR doers.

The FAIR Cookbook - the essential resource for and by FAIR doers.

The FAIR Cookbook - the essential resource for and by FAIR doers.

Predicting electricity demand profiles of new supermarkets using machine learning

Predicting electricity demand profiles of new supermarkets using machine learning

Helping the Consumers and Producers of Standards, Repositories and Policies to Enable FAIR Data

Helping the Consumers and Producers of Standards, Repositories and Policies to Enable FAIR Data

Implementation of a novel multi-agent system for demand response management in low-voltage distribution networks

Implementation of a novel multi-agent system for demand response management in low-voltage distribution networks

View all

Selected Publications

  • Granell, R.; Axon, C.J.; Kolokotroni, M.; Wallom, D.C.H; "A data-driven approach for electricity load profile prediction of new supermarkets"; 2nd International Conference on Sustainable Energy & Resource Use in Food Chains, Paphos (Cyprus), 2018
  • Pierrehumbert J.; Granell R.; "On hapax legomena and morphological productivity''; CoNLL–SIGMORPHON 2018, Brussels (Belgium), 2018
  • Granell, R.; Axon, C.J.; Kolokotroni, M.; Wallom, D.C.H; "Using existing building stock to predict the electricity load profiles of new supermarkets". Energy Systems Conference 2018, London (UK), 2018
  • Granell, R.; Axon, C.J.; Kolokotroni, M.; Wallom, D.C.H.; "Does the London urban heat island affect electricity consumption of small supermarkets?" Manchester Energy and Electrical Power Systems "Big Data Applications in Power Systems" Workshop. Manchester (UK), 2017
  • Granell, R.; Wallom D.C.H.; Janda, K.B.; Patrick J.; Bright S.; "Quantifying the impact of green leasing on energy use in a retail portfolio: limits to big data analytics" In: Proceedings of European Council for an Energy-Efficient Economy Summer Study. Presqu'ile de Giens (France), 2017
  • Miranda, N.D.; Granell, R.; Tuomisto, H.L.; McCulloch M.; "Meta-analysis of methane yields from anaerobic digestion of dairy cattle manure." Biomass and Bioenergy, Vol. 86:pp 65-75, 2016. DOI: http://dx.doi.org/10.1016/j.biombioe.2016.01.012
  • Granell, R.; Axon, C.J.; Wallom, D.C.H.; Layberry, R.L.; "Power-Use profile analysis of non-domestic premises for electricity tariff switching." Energy Efficiency, Vol 9(3):pp 825-841, 2016. DOI: http://dx.doi.org/10.1007/s12053-015-9404-9
  • Granell, R.; Axon, C.J.; Wallom, D.C.H.; "Clustering disaggregated load profiles using a Dirichlet process mixture model." Energy Conversion and Management, Vol 92: pp. 507-516, 2015. DOI: http://dx.doi.org/10.1016/j.enconman.2014.12.080
  • Granell, R.; Axon, C.J.; Wallom, D.C.H.; "Impacts of raw data temporal resolution using selected clustering methods on residential electricity load profiles." IEEE Trans. Power Systems, Vol 30(6): pp.3217-3224, 2015.DOI: http://dx.doi.org/10.1109/TPWRS.2014.2377213
  • Granell, R.; Axon, C.J.; Wallom, D.C.H.; "Predicting winning and losing businesses when changing electricity tariffs." Applied Energy, 133(C):298-307, 2014. DOI: http://dx.doi.org/10.1016/j.apenergy.2014.07.098

Most Recent Publications

The FAIR Cookbook - the essential resource for and by FAIR doers.

The FAIR Cookbook - the essential resource for and by FAIR doers.

The FAIR Cookbook - the essential resource for and by FAIR doers.

The FAIR Cookbook - the essential resource for and by FAIR doers.

Predicting electricity demand profiles of new supermarkets using machine learning

Predicting electricity demand profiles of new supermarkets using machine learning

Helping the Consumers and Producers of Standards, Repositories and Policies to Enable FAIR Data

Helping the Consumers and Producers of Standards, Repositories and Policies to Enable FAIR Data

Implementation of a novel multi-agent system for demand response management in low-voltage distribution networks

Implementation of a novel multi-agent system for demand response management in low-voltage distribution networks

View all