Senior Researchers
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PhDs
Past Students
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Pierre Mercatoris
France Regional Electricity Consumption Clustering Using Generalized Cross Correlation
Characterization of the twelve French regions taking into account their cross-dependencies. -
Fernando A. Hernández
Forecasting hourly-consumption for electricity smart meters using neural networks
Massive time-series forecasting based on LSTMs. -
Estelita Simoes Ribeiro
Automatic tool for short-term electricity consumption forecasting in UC3M
Load forecasting at low aggregate level based on advanced time series methods and machine learning tools. -
Oscar Blanco
Pollution forecasting for air quality management: an application in Madrid using open data
Automatic tool to predict hourly Madrid air-pollution on a daily basis, using time series and machine learning tools. Automatic app
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Manuel de Cesar
Short-term traffic forecasting in Madrid
Automatic spatial prediction of hourly Madrid traffic on a daily basis, using time series and machine learning tools. Automatic app
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JingHua Li
Short-term air pollution forecasting in cities with high contamination.
Automatic tool to predict hourly air-pollution levels in several cities all around the world on a daily basis, using time series and machine learning tools. Automatic app
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Ramón Nieto
Probabilistic forecasting of Spanish electricity hourly-demands in the medium term.
Automatic tool for probabilistic forecasting (medium-term) of electricity demands in Spain on an hourly basis, using time series and machine learning tools. -
Pablo Orazi
Forecasting Spanish electricity demand by technology and its relation with pool price.
Automatic tool to predict (short/medium) electricity demand in Spain with the associated generation technology mix on a daily basis, using time series and machine learning tools. Automatic app
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Aldo Ramón Franco
Spanish electricity price forecasting
Automatic tool to predict (short/medium/large) electricity prices in Spain on a daily basis, using time series and machine learning tools. -
Miguel Rodriguez
Using smart meter data for load forecasting at the local level in Smart grids.
Analytical tool to predict hourly electricity consumption on a daily basis and on a highly disaggregate level. -
Juan Sebastián Salcedo
Clustering and Predicting Time Series of Electricity Demand.
Analytical tool to predict predict the hourly energy demand in eight load zones of New England, United States, based on factor models and clustering.