Lucas Rizzo is a Ph.D. candidate at Dublin Institute of Technology, funded by the Brazilian Scholarship Science Without Borders. He has a BSc in Computational Mathematics and a Master's degree in Computer Science from Universidade Federal de Minas Gerais (UFMG - Brazil). In the past, he has worked in the fields of constraint programming and operational research, with four years of industry experience. Currently, his Ph.D. project is focused on defeasible reasoning and computational argumentation theory. It aims to demonstrate the impact of practical argumentation theory when compared to other knowledge driven approaches in areas such human mental workload, computational trust and health-care.
. RIZZO, Lucas et al.; An Investigation of Argumentation Theory for the Prediction of Survival in Elderly
Using Biomarkers. In: IFIP International Conference on Artificial Intelligence Applications and Innovations.
Springer, Cham, 2018. p. 385-397.
. RIZZO, Lucas.; On Demonstrating the Impact of Defeasible Reasoning in Practice via a Multi-layer
Argument-based Framework. In: Proceedings of the 16th Conference on Autonomous Agents and MultiAgent
Systems. International Foundation for Autonomous Agents and Multiagent Systems, 2017. p. 1857-1858.
. RIZZO, L., LONGO, L.; Representing and inferring mental workload via defeasible reasoning: a
comparison with the NASA Task Load Index and the Workload Profile. 1st Workshop on Advances In
Argumentation In Artificial Intelligence, Bari, Italy, 2017.
. RIZZO, Lucas, et al.; Modeling Mental Workload Via Rule-Based Expert System: A Comparison with
NASA-TLX and Workload Profile. IFIP International Conference on Artificial Intelligence Applications and
Innovations. Springer International Publishing, 2016.
Gave talk at AIAI 2018, Rhodes, Greece
Computational argumentation theory, defeasible reasoning, knowledge representation, fuzzy reasoning,
human mental workload