KAVKA Carlos

Head of Group

Unit: Reliable Distributed Systems

Group: Optimisation and Decision Systems

Languages: English, Slovenian, Spanish, Italian

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About

Carlos Kavka is the Group Leader of the Optimization and Decision-Making Group (OPTIMISE) within the Science Directorate at the Luxembourg Institute of Science and Technology (LIST). He holds a PhD in Computer Science from the Université Paris Sud (France). Carlos has served from 2008 to 2021as the Head of Research and Development at ESTECO SpA (Italy), a leading company specialized in multi-objective design optimization. In parallel, he contributed to academia as a Lecturer in Data Science and Scientific Computation at the University of Trieste (Italy) between 2019 and 2021. Prior to that, he made contributions as an Instructor, Lecturer, and co-Director of international workshops at the International Centre for Theoretical Physics (ICTP) in Italy from 1993 to 2012. Additionally, Carlos held the position of Professor at the Universidad Nacional de San Luis (Argentina) from 1994 to 2005. His activities in research also includes a participation in the LHC-CMS experiment at CERN (Geneve) from 2005 to 2007.

Latest Publications

Practical design and implementation of an augmented reality based digital twin

Protin L., Aggoune-Mtalaa W., Kavka C.

Proceedings Models 2024 ACM IEEE 27th International Conference on Model Driven Engineering Languages and Systems Companion Proceedings, pp. 459-463, 2024

MBCO: The Materials-Based Business Case Ontology from BPMN-EMMO Integration

Feltus C., Klein P., Konchakova N., Nicolas D., Kavka C., Horsch M.T., Preisig H.A., Khadraoui D., Belouettar S.

Lecture Notes in Business Information Processing, vol. 504 LNBIP, pp. 23-45, 2024

Towards Enhancing Open Innovation Efficiency: A Method for Ontological Integration of BPMN and EMMO

Feltus C., Nicolas D., Kavka C., Khadraoui D., Belouttar S., Konchakova N., Preisig H.A., Klein P.

Proceedings of the 18th Conference on Computer Science and Intelligence Systems Fedcsis 2023, pp. 471-479, 2023

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