Computer Science

The main goal of the third degree of the Informatics study programme is to prepare students for independent scientific and research work in the field of informatics, whether in an academic environment or in corporate development teams. The focus is on the ability to independently analyse and solve scientific and technical problems which, due to their complexity and difficulty, represent the limits of current knowledge.

Graduates of the program possess an extensive portfolio of mathematical techniques that allow them to formalize and then rigorously investigate and analyze even non-standard complex systems. They have deep theoretical and methodological knowledge of the key areas of computer science, corresponding to the current level of the research. In the focus area of their dissertation, graduates are proficient in the latest scientific techniques and procedures, and are familiar with the current state of research and development at the frontiers of the state of the art. They understand the connections and relationships among different areas of computer science and IT practice, and can apply thier insight to solve specific problems.

The study enables students to engage in research at the top international level, while mastering the principles of independent and team-based scientific work, the methodology of scientific research, the methods of formalizing problems and formulating results. They learn to publish their results in the form of a scientific text, and present them to the international scientific community. Participation in teaching activities is also an important part of the study, where the students acquire the ability to present complex results clearly, and comprehensibly, to formulate and communicate them appropriately.

The program provides students with the opportunity to specialize in a wide range of areas, from the mathematical foundations of computer science, through theoretical computer science, application areas such as computer security, computer vision, and the semantic web, to the latest directions in bioinformatics, machine learning, and computational cognitive science. Graduates of the programme are prepared to develop their discipline as independent researchers, able to lead research teams, follow the latest research trends in their field and formulate new research questions. They are also prepared to creatively apply acquired knowledge and techniques as members of research and development teams to solve practical problems. Their ability to understand and formally describe even non-standard complex systems makes them valuable members of interdisciplinary teams. They will be able to complement and update their knowledge through lifelong learning. They aware of the ethical, legal and social implications of their profession.

A study programme is a set of courses and a set of rules designed in such a way that successful completion of the courses, while observing the stated rules, enables the student to obtain a university degree. For each study programme there is a recommended plan of study, which is designed to ensure that by completing it the student meets the conditions for successful completion of his or her studies within the standard length of the programme.

The curriculum is usually based on the modular (block) principle in order to allow students to continuously modify the focus within the chosen field of study and to expand the scope of study. The curriculum is divided into compulsory, optional and elective courses. Courses are made up of individual particular learning activities or a combination of them, which are aimed at providing education in a defined area. Profile courses of the study plan are compulsory or compulsory elective courses and after their completion the student acquires knowledge and skills that are essential for graduation from the study programme.

Study programmes are augmented by elective courses, reflecting the developments in the field. Elective courses also allow the use of participation of non-faculty experts in the teaching process. The inclusion of more (elective) courses in the programmes is often response to constructive comments from students and their interest in a particular area.

The study part consists of the compulsory courses "Theoretical Foundations of Informatics" (8kr), "Theory and Methodology of Informatics" (10kr), "Specialization Area" (14kr) and "Literature Monitoring and Processing" (10kr) and is concluded with a dissertation examination (20kr). The content of the courses in each year is adapted to the composition of the PhD students; in a particular year, the content of the courses is chosen to convey to the students advanced knowledge of the theoretical principles of computer science and to enable them to gain a deep insight into areas that are broadly related to the area of their dissertation. At the same time, the student should acquire such knowledge in the area of specialization that enables active research in it. Also, the student will acquire the ability to actively follow the latest research developments in the relevant field, to understand, process and present the latest results. In this part of the curriculum, the supervisor may also prescribe the student to take additional courses from other programmes, if they are necessary in relation to the topic of the dissertation.

The scientific part is a key part of the educational process in the study programme, the aim of which is to prepare the student for independent research work. The supervisor plays an essential role here. In the curriculum, this part is represented by the course "Research Activity" in three variants with different credit ratings, which can be taken more than once and the student must obtain at least 50 credits from it. Since the Computer Science programme provides a wide range of specialisations in areas with different publishing habits, the final assignment of credits to specific outputs is determined by the supervisor, who ensures that the student measurably documents the work done, corresponding to the credit allocation. Typically, this includes the publication of technical reports, preprints, publication/submission of papers to conferences and journals, and similar outputs that document the student's progress in the preparation of the dissertation. The student is encouraged to present his/her scientific results at a national or international conference, and the supervisor may take all of these and similar activities into account in the evaluation of scientific activity. Regular active participation in scientific seminars within the relevant department or research group is also an essential part of the scientific training. The student is obliged to participate in a selected seminar according to his/her specialisation (e.g. Computer Security Seminar, Graph Theory Seminar, Theoretical Computer Science Seminar, CNC: Cognition and Neural Computation Seminar, YACGS: "Yet another Computer Graphics Seminar", Bioinformatics Seminar), where active participation is associated with regular presentation of results. Mobility experience through foreign and domestic study stays in scientific and scientific-educational institutions is also encouraged.

Graduates are primarily employable:

• in academia as independent researchers or assistant professors. Graduating from the programme and obtaining a PhD enables them to further pursue academic career in universities and research institutes in Slovakia and abroad. 
• in technology companies and research consortia, where the ability to develop software products using the latest technologies, to react to current research directions, to actively develop them and to transfer them into practice is required from the position of software developer, project manager, manager, consultant, etc.

During the doctoral studies, the student is an important part of the scientific team, where he or she works with the supervisor to solve complex scientific problems. The student is often responsible for managing and solving some of the sub-tasks, which require him/her to be able to organize teamwork (undergraduates and graduates) and to communicate appropriately with team members, and with foreign partners. Therefore, in addition to professional qualities, the student will also acquire auxiliary communication and language skills that can be applied in a wide range of professions.

prof. RNDr. Ľubica Beňušková, PhD.
doc. Mgr. Bronislava Brejová, PhD.
prof. RNDr. Roman Ďurikovič, PhD.
prof. Ing. Igor Farkaš, Dr.
doc. RNDr. Andrej Ferko, CSc.
doc. RNDr. Damas Gruska, PhD.
doc. RNDr. Dušan Guller, PhD.
doc. RNDr. Martin Homola, PhD.
doc. RNDr. Tatiana Jajcayová, PhD.
prof. RNDr. Rastislav Královič, PhD.
prof. RNDr. Mária Lucká, PhD.
doc. RNDr. Robert Lukoťka, PhD.
doc. Mgr. Tibor Macko, PhD.
doc. RNDr. Martin Mačaj, PhD.
doc. RNDr. Edita Mačajová, PhD.
doc. RNDr. Mária Markošová, PhD.
doc. RNDr. Ján Mazák, PhD.
doc. RNDr. Daniel Olejár, PhD.
doc. RNDr. Dana Pardubská, CSc.
doc. Dr. Tomáš Plachetka
doc. Ing. Ivan Polášek, PhD.
prof. RNDr. Branislav Rovan, PhD.
doc. RNDr. Elena Šikudová, PhD. (Karlova Univerzita Praha)
prof. RNDr. Martin Škoviera, PhD.
doc. RNDr. Martin Stanek, PhD.
doc. RNDr. Martin Takáč, PhD.
doc. Mgr. Tomáš Vinař, PhD.

• Computational analysis of large-scale datasets related to multiple sclerosis
  (supervisor: doc. Mgr. Bronislava Brejová, PhD.)
• Computationl analysis of bacterial plasmids
  (supervisor: doc. Mgr. Bronislava Brejová, PhD.)
•  Deep learning methods for medical image analysis
  (supervisor: RNDr. Zuzana Černeková, PhD.)
• Advertisement saliency detection
  (supervisor: RNDr. Zuzana Černeková, PhD.)
• Road traffic and vehicle analysis
  (školiteľka: RNDr. Zuzana Černeková, PhD.)
• Science Image Recognition Algorithms for all-sky Meteor Camera Systems
  (supervisor: prof. RNDr. Roman Ďurikovič, PhD., consultant: doc. RNDr. Juraj Tóth, PhD.)
• Mirroring mechanisms for trustworthy human-robot interaction
  (supervisor: prof. Ing. Igor Farkaš, Dr.)
• Efficient low-resource Natural Language Processing in Slovak
  (supervisor: prof. Ing. Igor Farkaš, Dr.)
• Virtual Museum Activisation and Usability
  (supervisor: doc. RNDr. Andrej Ferko, PhD.)
• Safety, security, privacy and its quantification
  (supervisor: doc. RNDr. Damas Gruska, PhD.) 
• Security - formal approach
  (supervisor: doc. RNDr. Damas Gruska, PhD.)
• Biologically motivated computational models
  (supervisor: doc. RNDr. Damas Gruska, PhD.) 
• Formal methods for verifications and specifications of concurrent and parallel systems
  (supervisor: doc. RNDr. Damas Gruska, PhD.) 
• Automated detuction in many-valued logics
  (supervisor: doc. RNDr. Dušan Guller, PhD.)
• Malware Detection Based on Explainable Al
  (supervisor: doc. RNDr. Martin Homola, PhD.)
• Abductive reasoning with ontologies in description logics
  (školiteľ: doc. RNDr. Martin Homola, PhD.)
• Automata and Algorithmis problems in Algebra
  (supervisor: doc. RNDr. Tatiana Jajcayová, PhD.)
• On the interplay between global and local symmetries
  (supervisor: doc. RNDr. Tatiana Jajcayová, PhD.)
• Models of computation: Non-uniformity and Data-dependence
  (supervisor: prof. RNDr. Rastislav Královič, PhD.)
• Algorithms on cubic graphs
  (supervisor: doc. RNDr. Robert Lukoťka, PhD.)
• Edge colourings and some conjectures in graph theory
  (supervisor: doc. RNDr. Edita Mačajová, PhD.)
• Relations between the structure and combinatorial invariants for classes of cubic graphs
  (supervisor:doc. RNDr. Edita Mačajová, PhD., consultant: RNDr. Ing. František Kardoš, PhD.)
• Modeling nanopore signals
  (supervisor: doc. Mgr. Tomáš Vinař, PhD.)
• Fundamental properties of information and complexity of problems
  (supervisor: prof. RNDr. Branislav Rovan, PhD.)

Institute of Informatics SAS:  

• Computer modelling of fires
  (supervisor: RND. Ján Glasa, CSc., email: jan.glasasavba.sk, consultant: Ing. Lukáš Valášek, PhD.)
• Distibuted large data processing
  (supervisor: doc. Ing. Ladislav Hluchý, CSc., email: ladislav.hluchysavba.sk)
• Artificial Intelligence Methods in Cyber Security
  (supervisor: doc. Ing. Ladislav Hluchý, CSc., email: ladislav.hluchysavba.sk)
• Automatic detection of Alzheimer´s disease by patient speech analysis
  (supervisor: Ing. Milan Rusko, PhD., email: rusko.uisavba.sk)
• Automatic measurement of stress in human voice
  (supervisor: Ing. Milan Rusko, PhD., email: rusko.uisavba.sk)
• High-end expressive speech synthesis in Slovak
  (supervisor: Ing. Milan Rusko, PhD., email: rusko.uisavba.sk)
• New methods for development, deployment and orchestration of cloud services
  (supervisor: Ing. Dinh Viet Tran, PhD., email: viet.transavba.sk)
• Computer modelling of flows in road tunnel during fire
  (supervisor: Mgr. Peter Weisenpacher, PhD., email: weisenpacher.uisavba.sk)