Dr. Luca Longo
luca.longo@tudublin.ie
Member of the Applied Social Computing Research group
Lecturer in Computer Science, TU Dublin
- Machine Learning, Explainable Artificial Intelligence, Human-Computer Interaction
Dr. Luca Longo is an early stage scientist deeply devoted and highly passionate for science. He strives for excellence and contribution to knowledge. He is a curious person, hungry of knowledge, as his never-ending education demonstrates. Since he started his undergraduate studies, Luca’s interests have always revolved around Artificial Intelligence and innovative applications, especially applied to formal reasoning and the World Wide Web. Luca has completed a BSc (honours) and an MSc (awarded distinction) both in Computer Science at the University of Insubria (Varese, Italy). He has obtained also a Postgraduate Diploma in Statistics and an MSc in Health Informatics (awarded distinction) at the University of Dublin, Trinity College (Ireland). In Trinity Luca as also successfully defended his PhD thesis in Artificial Intelligence. Additionally, he has recently obtained a Postgraduate diploma in Learning and Teaching at TU Dublin as well as an MSc in Applied e-Learning.
Luca is a lecturer, covering both MSc and PhD courses in Computer Science and he’s the leader of a team of post-graduated talented individuals working in Artificial Intelligence. He’s actively engaged in the dissemination of scientific material Luca received various awards both for his research work and for his teaching and pedagogical practices. In 2016 Luca was awarded a “national teaching hero award” from the national forum of teaching and learning in Ireland.
Luca obtained the following qualifications:
Doctor of Philosophy in Computer Science (PhD, level 10) Trinity College Dublin [Sept.. 2008/2013]
Master in applied e-learning (MSc, level 9) Dublin Institute of Technology [Sept. 2015/2018]
Master of Science, Health Informatics (MSc, level 9) Trinity College Dublin (awarded distinction) [Sept. 2010/2012]
Master in Computer Science (MSc, level 9) Insubria University (awarded ‘summa cum Laude’) [Sept. 2005/2007]
Bachelor in Computer Science (BSc, level 8, honour) Insubria University [Sept. 2002/2005]
Postgraduate Diploma in Learning & Teaching (PgDip, level 9) Dublin Institute of Technology [Sept. 2014/2015]
Postgraduate Diploma in Statistics (PgDip, level 9) Trinity College Dublin [Sept. 2008/2009]
Alongside his academic path, for the last 20 years Luca has been designing and developing software solutions at various levels adopting different programming languages, technologies and methodologies. Back to the nineties, his early passion for code got increasingly more vigorous and fine-grained with several experiences as software developer in international software houses. In the last decade, Luca has covered the position of software architect and technology leader in a couple of start-ups. He is actively engaged in the dissemination of scientific material, as his many interviews on televisions, radio and various press media, as well as my TEDx talks demonstrate.
Luca is an early stage scientist deeply devoted and highly passionate for science. His vision is to formalise the ill-defined construct of human Mental Workload as a computational concept through deductive knowledge representation and reasoning techniques (Defeasible Reasoning, Argumentation Theory) and inductive modelling techniques (Machine Learning), coupled with ideas coming from Explainable Artificial Intelligence (XAI). Field of applications includes Human-Computer Interaction, Education, NeuroScience, Universal Design.
Luca have been developing a strong international network since 2013 with:
Ireland
[2019/-] ML-Labs, the Centre for Research Training in Machine Learning, Science Foundation Ireland, Republic of Ireland
[2019/-] D-REAL, the Centre for Research Training in Digitally-Enhanced Reality, Science Foundation Ireland Republic of Ireland
[2016/-] Centre for Innovative Human Systems, School of Psychology, The University of Dublin, Trinity College
[2015/-] The Centre For Excellence in Universal Design, the Irish National Disability Authority
[2015/-] ADAPT, the global centre of excellence for digital content/media innovation, Science Foundation Ireland, Republic of Ireland
[2013/-] The Applied Intelligence Research Centre, Technological University Dublin, Republic of Ireland
Russia
Innopolis University, Innopolis, Khazan, Republica Of Tatarstan, Russia
Longo L., Rizzo L., Dondio P. Examining the modelling capabilities of defeasible argumentation and non-monotonic fuzzy reasoning, Knowledge-Based Systems, 2021, V. 211, 106514
Rizzo, L., Longo L. An empirical evaluation of the inferential capacity of defeasible argumentation, non-monotonic fuzzy reasoning and expert systems, Expert Systems with Applications, 147: 113-220, Elsevier
Longo L. Experienced mental workload, perception of usability, their interaction and impact on task performance. PLoS ONE 13(8), 2018: e0199661. https://doi.org/10.1371/journal.pone.0199661
Longo L., A defeasible reasoning framework for human mental workload representation and assessment Behaviour & Information Technology. 34(8), pp. 758-786, 2015 Taylor & Francis
Longo L., Dondio P., Barrett S. – Enhancing Social Search: a Computational Collective Intelligence Model of Behavioural Traits, Trust and Time – Special issue Transactions on Computational Collective Intelligence of the Volume 6450 of the series Lecture notes in Computer Science, pp. 46-69, 2010. ISBN: 978-3-642-17154-3
Dondio P., Longo L. Beyond reasonable doubt: a proposal for undecidedness blocking in abstract argumentation, Intelligenza Artificiale, 13(2), 123-135, 2019
Longo L. Argumentation for knowledge representation, conflict resolution, defeasible inference and its integration with machine learning. Book Chapter in Machine Learning for Health Informatics. Springer Volume 9605 of the series Lecture Notes in Computer Science pp 183-208
Longo L. Empowering qualitative research methods in education with artificial intelligence. in WCQR 2019: Computer Supported Qualitative Research pp 1-21, volume 1068, Springer
Orru G., Longo L. The Evolution of Cognitive Load Theory and the Measurement of Its Intrinsic, Extraneous and Germane Loads: A Review. Longo, L., & Leva, M. C. (Eds.). (2018) Second International Symposium, H-WORKLOAD 2018, Amsterdam, The Netherlands, September 20-21, 2018, Revised Selected Papers (vol. 1012), pp. 23-48
Longo L, Goebel R., Lecue F., Kieseberg P., Holzinger A. Explainable Artificial Intelligence: concepts, applications, research challenges and visions CD-MAKE 2020: 1-16, Springer