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My research interests are transversal to several topics in the multi-disciplinary field of data science, including, but not limited to, instrumentation and data acquisition, public data, machine learning, and information visualization. My research is driven by curiosity, persistence, and a strong desire to leverage the potential of data to address different societal challenges like environmental sustainability and smart cities. A brief outline of my current research topics is provided below.

Performance and Value Proposition of Disaggregated Energy Consumption Data

I am very interested in understanding the real-world applicability of non-intrusive energy monitoring and eco-feedback technologies and my goals in this research field are twofold: i), assess how such technologies perform from a technological point of view (e.g., algorithms performance) when deployed outside of the laboratory settings, and ii) determine the value proposition of such technologies as tools for smartening the electric energy grid hence reducing its carbon footprint.

Integration of Renewable Energy Sources (RES) and Electric Vehicles (EV)

Under this topic,  my research goals are three-fold: i) understand how individual appliance consumption data, daily routines, and Battery Energy Storage Systems (BESS) can be leveraged to maximise the self-consumption from RES in households and small businesses, ii) understand how driving and daily routines, individual appliance consumption data, and BESS can be leveraged to develop frameworks for charging EVs in individual households and residential buildings, and iii) understand how BESS and EVs can be combined to mitigate voltage and frequency control issues that may occur due to the intermittent nature of RES.


  • Future Energy Systems
  • Computational Sustainability
  • Water-Energy-Food Nexus
  • Real-world Deployments
  • Performance Evaluation
  • Data Science
  • Machine-Learning
  • Human-Computer Interaction


Further Energy and Environment research Laboratory

I am currently leading the Further Energy and Environment research Laboratory (FEELab), at ITI/LARSyS.

In FEELab we FEEL the need for a more sustainable planet, as such the main focus of this research group is to work towards addressing the different societal challenges under the UN Sustainable Development Goals. We do this by leveraging the potential of computer science, data science, and human-computer interaction research.


Luísa Barros

Luísa Barros

PhD Student (@ University of Madeira)

Future Energy Systems: Smart Charging of Electric Vehicles in Isolated Grids
João Góis

João Góis

PhD Student (@ Técnico Lisboa)

Performance Evaluation: On the Relationship Between Similarity Measures and Complexity in Energy Disaggregation
Anthony Faustine

Anthony Faustine

PhD Student (@ Técnico Lisboa)

Future Energy Systems: Towards Robust Machine Learning Algorithms for Future Energy Systems
Donovan Costa

Donovan Costa

MSc Student (@ University of Madeira)

Performance Evaluation: Semi-automatic Collaborative Labeling of NILM Datasets
Manuel Pereira

Manuel Pereira

MSc Student (@ University of Madeira)

Computational Sustainability
Nuno Velosa

Nuno Velosa

MSc Student (@ University of Madeira)

Future Energy Systems

FEELab is constituted by a team of bright, young, and talented students and researchers.

Interested in collaborating? Drop me an email.

Research Grants

So far, my research in collaboration with other members from M-ITI / LARSYS and, has led to the successful application of four Research & Development grants.

Currently Funded Projects


    SMart IsLand Energy systems

    Role: Co-PI at,


    Duration: May 2017 to April 2021

    Funding Agency: EU / H2020-LCE-2016-SGS

    Reference: 731249

    Total Funding: ~12M €

Previously Funded Projects

  • FIK

    Design of industrial kitchen of the future: innovation with Internet of Things (IoT) and active intelligent technologies

    Role: Senior researcher

    Duration: October 2018 to September 2019

    Funding Agency: Madeira 14-20 / FEDER

    Reference: M1420-01-0247-FEDER-000018

    Total Funding: ~431k €

  • Energy Spectrum

    Market uptake of an innovative Non-intrusive Appliance Load Monitoring (NIALM) to enlarge ENERGY efficiency SPECTRUM to comprise the families factor

    Role: Data Science Lead at


    Duration: February 2016 to July 2016

    Funding Agency: EU / H2020-SMEINST-1-2015

    Reference: 710936

    Total Funding: ~71k €

  • SmartSolar

    Smart Solar Energy Management and Monitoring

    Role: Senior Researcher

    Duration: September 2014 to August 2015

    Funding Agency: Madeira Region II / + Conhecimento II

    Reference: MADFDR-01- 0190-FEDER-000015