HUMAD 2024: International Workshop on Human-Centered Modeling and Adaptation for Digital Transformation

Balloccu, Simone; Podda, Alessandro Sebastian; Pompianu, Livio; Saia, Roberto and Salatino, Angelo Antonio (2024). HUMAD 2024: International Workshop on Human-Centered Modeling and Adaptation for Digital Transformation. In: Adjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization (UMAP Adjunct ’24), July 01–04, 2024, Cagliari, Italy, ACM, New York, NY, USA.



While digital transformation brings broad positive impacts, its rapid propagation varies across territories, accentuating disparities not only in the social and organisational contexts but even in industrial sectors. Acknowledging this digital divide, the HUMAD workshop aimed to reshape industrial and digital landscapes for equity and accessibility, specifically emphasising the pivotal role of user modelling and artificial intelligence. Discussions centred on personalised user modelling and holistic, human-centred approaches tailored for an industrial context. The workshop explored applications in critical sectors, including smart cities, tourism, industrial production, healthcare, education, and well-being, focusing on delivering quality digital interactions and services tuned to industrial and human-centric needs. The objective was to elevate the quality of digital interactions and services, ensuring a more uniform and inclusive distribution of the benefits of industrial digital transformation. Beyond immediate concerns, HUMAD delved into user modelling’s potential to drive growth in disadvantaged territories. By comprehending the unique challenges these regions face, the aim was to cultivate sustainable solutions within an industrial framework. In the light of the above, we invited contributions that navigate the intricacies of user modelling, proposing innovative strategies to reduce disparities and develop a more equitable, human-centric digital future.

Viewing alternatives


Public Attention

Altmetrics from Altmetric

Number of Citations

Citations from Dimensions
No digital document available to download for this item

Item Actions