Name and surname:
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Ing. Alexander Šimko, PhD.
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Document type:
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Research/art/teacher profile of a person
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The name of the university:
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Comenius University Bratislava
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The seat of the university:
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Šafárikovo námestie 6, 818 06 Bratislava
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III.a - Occupation-position | III.b - Institution | III.c - Duration |
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assistant professor | Faculty of mathematics, physics and informatics, Comenius University Bratislava | 2014 - 2024 |
V.1.a - Name of the profile course | V.1.b - Study programme | V.1.c - Degree | V.1.d - Field of study |
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Databases (1) | Applied Computer Science | I | 18. - Computer Science |
Game Engines | Applied Computer Science | I | 18. - Computer Science |
Programming (3) | Applied Computer Science | I | 18. - Computer Science |
Logic for Computer Science | Applied Computer Science | I | 18. - Computer Science |
V.5.a - Name of the course | V.5.b - Study programme | V.5.c - Degree | V.5.d - Field of study |
---|---|---|---|
Game Engines (2) | Applied Computer Science | I | 18. - Computer Science |
A. Šimko: A descriptive handling of directly conflicting rules in preferred answer sets, Declarative Programming and Knowledge Management, 2014, 202-217
A. Šimko: A family of descriptive approach to preferred answer sets, Proceedings of the 15th International Workshop on Non-Monotonic Reasoning (NMR 2014), 2014, 223-232
A. Šimko: Extension of Gelfond-Lifschitz reduction for preferred answer sets : Preliminary report. Kiel Declarative Programming Days 2013. Kiel : Institut für Informatik, 2013. - S. 2-16 (Technische Berichte des Instituts für Informatik ; No. 1306)
Homola et al. Resolving conflicts in knowledge for ambient intelligence. Knowledge Engineering Review, 2015, 30(5), pp. 455–513.
A. Šimko: Accepting the natural order of rules in a logic program with preferences. Leibniz International Proceedings in Informatics, LIPIcs, 2011, 11, pp. 284–289.
T. Bisták et al. Improving DL-Learner on a Malware Detection. Proceedings of the 36th International Workshop on Description Logics. 2023.
P. Švec et al. Towards Explainable Malware Detection with Structured Machine Learning. 4th Workshop on Explainable Logic-Based Knowledge Representation. 2023, p. 1-7.
Ibrhim, H., Hassan, H., Nabil, E. A conflicts' classification for IoT-based services: a comparative survey. PeerJ Computer Science. 2021.
Liu, C., Park, E.-M., Jiang, F. Examining effects of context-awareness on ambient intelligence of logistics service quality: user awareness compatibility as a moderator. Journal of Ambient Intelligence and Humanized Computing. 2020.
Subagdja, B., Tan, A.-H., Kang, Y. A coordination framework for multi-agent persuasion and adviser systems. Expert Systems with Applications. 2019.
Oguego, C.L., Augusto, J.C., Muñoz, A., Springett, M. Using argumentation to manage users’ preferences. Future Generation Computer Systems. 2018.
Oguego, C.L., Augusto, J.C., Muñoz, A., Springett, M. A survey on managing users’ preferences in ambient intelligence. Universal Access in the Information Society. 2018.
Team member of: TAILOR Coordinated Action T3.1 Explainable malware/security threat detection. Objectives: (i) testing different algorithms able to provide explanations, e.g. DL Learner, xDNNs, (ii) reviewing other “classic” methods and their possible extension/hybridization towards explainability (iii) generalisation of the findings on other relevant areas
Team member of: ORBIS - Ontological representation for security of information systems. APVV. Goals: In the first phase of the project, collect and analyze relevant data from running information systems and collaborate with existing sharing platforms like MISP. In the second phase, we want to test methods for storing and sharing acquired data in ontological representations. Finally, we want to test the usability of ontological representation to acquire new knowledge and to detect malicious behavior.