Periodic Reporting for period 1 - TAMED (Tensor-bAsed Machine learning towards genEral moDels of affect)
Periodo di rendicontazione: 2020-07-01 al 2022-06-30
Since Picard’s seminal paper in 1995 (see R. Picard, “Affective Computing,” Technical Report (MIT Media Laboratory Perceptual Computing Section, Nov. 1995).), the Affective Computing (AC) field has advanced the study of modelling human affect substantially. Most modern approaches, however, indicate that any success of AC depends heavily on the domain, the task at hand, and the context in general. This specificity limitation is detrimental both to the scientific value and to the practical applicability of the methods developed and studied in the AC field. Deriving general “context-free” affect models is a crucial step towards understanding the inner workings of emotional intelligence, advancing AI agents and building better human-computer and human-robot interaction systems affecting the everyday lives of millions of people.
Based on the discussion above, the main objective of TAMED was to derive general models of affect and investigate the degree to which the construction of such models is possible. Towards this direction, research efforts focused on the entire cycle of affective modelling, starting with the definition of general input-output representations of context and affect, moving towards developing novel Machine Learning models, and validating the derived affect models on complex real-world problems.
During WP6, related to dissemination and communication activities, the Fellow 1) was the main organiser of the first “What’s Next In Affect Modelling?” workshop that took place within the International Conference on Affect Modelling and Intelligent Interaction (ACII 2021 – one of the most important annual meetings for the Affective Computing community). Also, after the successful first event, the Fellow will organise the second workshop in the series within ACII 2022, 2) served as Keynote Speaker at the 1st International Conference on Novelties in Intelligent Digital Systems (NIDS 2021), 3) delivered an invited talk at the University of West Attica on Machine Learning for High-Order Data Analysis, 4) served as a panel member for the UM Grants Week organised by the University of Malta (UM), the Malta Council for Science and Technology (MCST), the European University of the Seas (SEA-EU) and supported by EU Commission, 5) featured in Press Releases in Malta Business Weekly and THINK magazine, 6) delivered lectures for postgraduate IDG courses, and 7) co-supervised two early-stage researchers (PhD students). Finally, he published two journal papers and eight peer-reviewed conference papers under the “Green” open access model.
Finally, from the fellow’s perspective, during the grant, the Fellow 1) enhanced his professional network, 2) acquired teaching, mentoring and managerial skills, and 3) boosted his curriculum vitae with high-quality publications. All the activities he performed and the skills he acquired during the action were essential for his appointment as a Lecturer at the University of Malta (starting on September 1st 2022) and, thus, crucial for his career development.