Sambaiga

Hello I am Anthony Faustine a Senior Industrial Analytics Researcher, at Irish Manufacturing (IMR), Dublin, Ireland where I develop computational models, methods, and tools to help industries and manufacturing design more effective solutions. I have experience in applying data science and machine learning techniques to business problems with a track record in the delivery and management of AI projects in academia and industries. 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 Artificial Intelligence technical solutions for business problems.

I am also a PhD research 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. My research focus on developing robust machine learning algorithms for industrial applications with a specific focus on future energy systems.

Although I am a person who takes the initiative, I enjoy working as part of a team. I possess a strong team-work spirit with experience of working in a highly international environment. I have good critical and creative thinking, problem-solving, leadership, and project management skills with excellent scientific writing and presentation skills.

Research area

  1. Machine learning and signal processing for smart-energy systems with a focus on load monitoring and management, Community Energy and Smart Grid.
  2. Robust deep learning for industrial applications with a focus on a learning algorithms that allows uncertainty quantification, is robust to low data setting and allows self-supervised or semi-supervised learning.
  3. Artificial Intelligence for Industrial 4.0 with focus on preventive maintenance, machine vision and streaming analytics
  4. Artificial Intelligence for Earth Observations(EO) data with a focus on sustainable energy, agriculture and natural resources management.
  5. Data management with a focus on specification, strategies, best practises and guideline for machine learning training dataset development.

selected publications

  1. AWRGNILM
    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