I am Anthony Faustine, a Lead data scientist at the Centre of Intelligence Power (CIP) Eaton, Dublin. I have experience applying data science and machine learning techniques to business problems, with a track record in delivering and managing AI projects in academia and industries. Previously I was a Senior Industrial Analytics Researcher at Irish Manufacturing (IMR), Dublin, Ireland, where I developed data analytics solutions and tools to help industries and manufacturing design more effective solutions.

Between 2012 and 2017, I worked as an assistant lecturer at the University of Dodoma, Tanzania, where I was involved in several research projects within ICT for development (ICT4D). In 2017, I joined IDLab, imec research group of the University of Ghent in Belgium as a Machine learning researcher. From 1st February 2020 to 30th March 2021, I worked as a Data Scientist and Machine learning researcher at CeADAR (UCD), Dublin, Ireland, where I devised and implemented data analytics and AI technical solutions for business problems.

I am also PhD research Fellow at Further Energy and Environment Research Laboratory (FEELab), at ITI/LARSyS, Técnico Lisboa in Portugal under Prof Nuno Jardim Nunes and Dr. Lucas Pereira supervision. I am currently doing a Masters progam; MSc In Leadership, Innovation And Technology offered by TU Dublin (Grangegorman Campus) in partnership with Technology Ireland ICT.

My research focuses on developing robust machine-learning algorithms for real-world industrial applications, focusing on the following key areas.

  1. Machine learning and signal processing for time series analysis focusing on Energy-disaggregation, Power demand forecasting, Anomaly detection and predictive maintenance.
  2. Computer vision techniques for machine vision focusing on vision anomaly detection, shape matching and visual inspection.
  3. Artificial Intelligence and Earth Observations(EO) for sustainability focusing on sustainable energy, agriculture and natural resources management.
  4. Data management focuses on specification, strategies, best practices and guidelines for AI dataset development.

I also maintain a repository with resources on learning and applying AI for practical problems.

selected publications

  1. FPSeq2Q
    FPSeq2Q: Fully Parameterized Sequence to Quantile Regression for Net-Load Forecasting with Uncertainty Estimates
    Faustine, Anthony, and Pereira, Lucas
    IEEE Transactions on Smart Grid 2022
    Adaptive Weighted Recurrence Graphs for Appliance Recognition in Non-Intrusive Load Monitoring
    Faustine, Anthony, Pereira, Lucas, and Klemenjak, Christoph
    IEEE Transactions on Smart Grid 2021