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Open lecture "Computational models of Human Mental Workload: State of Science, Open problems, Challenges and Future perspectives". Speaker Dr. Luca Longo

description

The principal reason for measuring Mental Workload is to quantify the mental cost of performing tasks in order to predict human performance. In turn, prediction of performance can be used for designing interfaces, technologies, information processing activities and interactions better aligned to the human mental limited capacities. Despite these benefits, understanding the shape of the construct of Mental Workload, its core dimensions, their relationship and their impact on human performance are all open problems. In this seminar I will talk about the construct of Human Mental Workload, the state of science, open problems challenges and future perspectives.

Speaker’s bio

“Dr. Luca Longo is currently lecturer at Dublin Institute of Technology, where he is a member of the Applied Intelligence Research Center, a member of the ADAPT global centre of excellence for digital content and innovation and  MSc theses coordinator in the School of Computing. He is author of 30+ academic articles appeared in conference proceedings, book chapters, and journals in various theoretical and applied computer science fields. He is the founder of the first international symposium of human mental workload, models and applications.

His core research interest is in Mental Workload modelling using deductive inference techniques (Defeasible Reasoning, Argumentation Theory, Recommender/Expert systems) as well as knowledge discovery and inductive predictive modelling techniques (Supervised/Unsupervised Machine Learning). Domains of application of Mental Workload models include human-computer/web interaction (HCI), health-care (HC), education (EDU) and Universal Design (UD). In particular, computational models of mental workload can be used for designing, personalising and adapting technologies and multi-modal interactions, better aligned to the human mental limited capacities and in turn enhancing user engagement, satisfaction and learning.

Luca owns a BSc (honors) and a MSc (distinction) in Computer Science (Italy), a PostGraduate Diploma in statistics, a MSc (distinction) in Health Informatics and a PhD in Artificial Intelligence awarded at Trinity College Dublin. He also owns a post-graduate diploma in Learning and Teaching at Dublin Institute of Technology and completing an MSc in Applied e-Learning.”

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