The event is sponsored by the SATO and SMART2B projects and will be held virtually.
The workshop follows the success of the 2021 edition (MLBEM 2021) co-located with ECML-PKDD’2021. The workshop gained strong interest, with an attendance between 15 and 25 participants, lively discussions after the talks, and an excellent invited talk.
The session aims at filling a gap in the EU workshop panorama, providing researchers with a forum to exchange and discuss scientific contributions and open challenges, both theoretical and practical, related to the use of machine-learning approaches in building energy management. The purpose of this workshop is to foster collaborative work and knowledge sharing between the building energy community and researchers and practitioners in the field of machine learning and its connection to Big Data, data science, and visualization.
The event shall provide a forum for discussing novel trends and achievements in machine learning and their role in the development of scalable BEMs. It aims to highlight the latest research trends in machine learning, privacy of data, big data, deep learning, incremental and stream learning, and adversarial learning. In particular, it aims to promote the application of these emerging ML techniques to buildings energy management.
The workshop shall contribute to identify new application areas as well as open and future research problems related to the application of machine-learning in the building’s energy field.
For more informations about the workshop and the organizers follow this link.