Filipe Rodrigues

Technical University of Denmark — Denmark

Engineering · Physical Sciences

7h-index259citations14works0.32yr avg
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Research Topics

Energy Load and Power Forecasting(7), Building Energy and Comfort Optimization(5), Smart Grid Energy Management(5), Energy Efficiency and Management(3), Solar Radiation and Photovoltaics(2)

Publications14 total

Climate Surrogates for Scalable Multi-Agent Reinforcement Learning: A Case Study with CICERO-SCM
arXiv (Cornell University)·2025Open Access
A Bayesian latent class reinforcement learning framework to capture adaptive, feedback-driven travel behaviour
SSRN Electronic Journal·2025Open Access
A Multi‐Trip Vehicle Routing Problem With Release Dates and Interrelated Periods
Networks·2024· 1 cited
FADO: A Federated Learning Attack and Defense Orchestrator
2023· 2 cited
Short-Term Load Forecasting of Electricity Demand for the Residential Sector Based on Modelling Techniques: A Systematic Review
Energies·2023· 24 citedOpen Access
Home Energy Forecast Performance Tool for Smart Living Services Suppliers under an Energy 4.0 and CPS Framework
Energies·2022· 5 citedOpen Access
Modeling System Based on Machine Learning Approaches for Predictive Maintenance Applications
KnE Engineering·2020· 8 citedOpen Access
IMPROVING INDOOR AIR QUALITY OF NATURALLY VENTILATED CLASSROOMS IN THE NORTHEAST OF PORTUGAL
Environmental Engineering and Management Journal·2019· 4 citedOpen Access
Energy Household Forecast with ANN for Demand Response and Demand Side Management
Renewable Energy and Power Quality Journal·2017· 6 citedOpen Access
Neural Networks Applied to Short Term Load Forecasting: A Case Study
Smart innovation, systems and technologies·2017· 8 cited
Load Profile Analysis Tool for Electrical Appliances in Households Assisted by CPS
Energy Procedia·2016· 10 citedOpen Access
Family Houses Energy Consumption Forecast Tools for Smart Grid Management
Lecture notes in electrical engineering·2016· 8 citedOpen Access
3I Buildings: Intelligent, Interactive and Immersive Buildings
Procedia Engineering·2015· 24 citedOpen Access
The Daily and Hourly Energy Consumption and Load Forecasting Using Artificial Neural Network Method: A Case Study Using a Set of 93 Households in Portugal
Energy Procedia·2014· 159 citedOpen Access

Frequent Co-authors

Carlos Cardeira(7), J. M. F. Calado(7), Rui Melício(5), António Aguiar Costa(1), Pedro Mira Lopes(1), André Antunes(1), Izunildo Cabral(1), António Grilo(1), João Pedro Serrasqueiro Martins(1), Nuno Henriques(1), Manuel Feliciano(1), Rodrigo Simões(1), Nuno Neves(1), Raquel Bernardino(1), João Janela(1), Carlos Martins(1), Maria Cândida Mourão(1), Leonor Santiago Pinto(1), Oskar Bohn Lassen(1), Serio Agriesti(1)