Combined study

4 years

prof. Ing. Zdeněk Smékal, CSc.

Chairman :
prof. Ing. Zdeněk Smékal, CSc.
Councillor internal :
doc. Ing. Radim Burget, Ph.D.
prof. Ing. Jiří Mišurec, CSc.
doc. Ing. Vladislav Škorpil, CSc.
doc. Ing. Jiří Hošek, Ph.D.
prof. Ing. Jaroslav Koton, Ph.D.
Councillor external :
doc. Ing. Otto Dostál, CSc.
prof. Ing. Boris Šimák, CSc.
prof. Ing. Ivan Baroňák, Ph.D.

The student is fostered to use the theoretical knowledge and experience gained through own research activities in an innovative manner. He is able to efficiently use the gathered knowledge for the design of own and prospective solutions within their further experimental development and applied research. The emphasis is put on gaining both theoretical and practical skill, ability of self-decisions, definition of research and development hypotheses to propose projects spanning from basic to applied research, ability to evaluation of the results and their dissemination as research papers and presentation in front of the research community.

The doctor study program "Teleinformatics" aims to generate top research and development specialists, who have deep knowledge of principles and techniques used in communication and data wired and wireless networks and also in related areas and also in data/signal acquisition, processing and the back representation of user data on the level of application layer. The main parts of the studies are represented by areas dealing with information theory and communication techniques. The graduate has deep knowledge in communication and information technologies, data transfer and their security. The graduate is skilled in operation systems, computer languages and database systems, their usage and also design of suitable software and user applications. The graduate is able to propose new technology solution of communication tools and information systems for advanced transfer of information.

Graduates of the program "Teleinformatics" apply in particular in research, development and design teams, in the field of professional activity in production or business organizations, in the academic sphere and in other institutions involved in science, research, development and innovation, in all areas of the company where communication systems and information transfer through data networks are being applied and used.
Our graduates are particularly experienced in the analysis, design, creation or management of complex systems aimed for data transfer and processing, as well as in the programming, integration, support, maintenance or sale of these systems.

Doctoral studies are carried out according to the individual study plan, which will prepare the doctoral student in cooperation with the doctoral student at the beginning of the study. The individual study plan specifies all the duties stipulated in accordance with the BUT Study and Examination Rules, which the doctoral student must fulfill to successfully finish his studies. These responsibilities are time-bound throughout the study period, they are scored and fixed at fixed deadlines. The student enrolls and performs tests of compulsory courses, at least two obligatory elective subjects with regard to the focus of his dissertation, and at least two elective courses (English for PhD students, Solutions for Innovative Entries, Scientific Publishing from A to Z).
The student may enroll for the state doctoral exam only after all the tests prescribed by his / her individual study plan have been completed. Before the state doctoral exam, the student prepares a dissertation thesis describing in detail the goals of the thesis, a thorough evaluation of the state of knowledge in the area of ​​the dissertation solved, or the characteristics of the methods it intends to apply in the solution. The defense of the controversy that is opposed is part of the state doctoral exam. In the next part of the exam the student must demonstrate deep theoretical and practical knowledge in the field of microelectronics, electrotechnology, materials physics, nanotechnology, electrical engineering, electronics, circuit theory. The State Doctoral Examination is in oral form and, in addition to the discussion on the dissertation thesis, it also consists of thematic areas related to compulsory and compulsory elective subjects.
To defend the dissertation, the student reports after the state doctoral examination and after fulfilling conditions for termination, such as participation in teaching, scientific and professional activity (creative activity) and at least a monthly study or work placement at a foreign institution or participation in an international creative project .

The doctoral studies of a student follow the Individual Study Plan (ISP), which is defined by the supervisor and the student at the beginning of the study period. The ISP is obligatory for the student, and specifies all duties being consistent with the Study and Examination Rules of BUT, which the student must successfully fulfill by the end of the study period. The duties are distributed throughout the whole study period, scored by credits/points and checked in defined dates. The current point evaluation of all activities of the student is summarized in the “Total point rating of doctoral student” document and is part of the ISP. At the beginning of the next study year the supervisor highlights eventual changes in ISP. By October, 15 of each study year the student submits the printed and signed ISP to Science Department of the faculty to check and archive.
Within the first four semesters the student passes the exams of compulsory, optional-specialized and/or optional-general courses to fulfill the score limit in Study area, and concurrently the student significantly deals with the study and analysis of the knowledge specific for the field defined by the dissertation thesis theme and also continuously deals with publishing these observations and own results. In the follow-up semesters the student focuses already more to the research and development that is linked to the dissertation thesis topic and to publishing the reached results and compilation of the dissertation thesis.
By the end of the second year of studies the student passes the Doctor State Exam, where the student proves the wide overview and deep knowledge in the field linked to the dissertation thesis topic. The student must apply for this exam by April, 30 in the second year of studies. Before the Doctor State Exam the student must successfully pass the exam from English language course.
In the third and fourth year of studies the student deals with the required research activities, publishes the reached results and compiles the dissertation thesis. As part of the study duties is also completing a study period at an abroad institution or participation on an international research project with results being published or presented in abroad or another form of direct participation of the student on an international cooperation activity, which must be proved by the date of submitting the dissertation thesis.
By the end of the winter term in the fourth year of study students submit the elaborated dissertation thesis to the supervisor, who scores this elaborate. The final dissertation thesis is expected to be submitted by the student by the end of the fourth year of studies.
In full-time study form, during the study period the student is obliged to pass a pedagogical practice, i.e. participate in the education process. The participation of the student in the pedagogical activities is part of his/her research preparations. By the pedagogical practice the student gains experience in passing the knowledge and improves the presentation skills. The pedagogical practice load (exercises, laboratories, project supervision etc.) of the student is specified by the head of the department based on the agreement with the student’s supervisor. The duty of pedagogical practice does not apply to students-payers and combined study program students. The involvement of the student in the education process within the pedagogical practice is confirmed by the supervisor in the Information System of the university.

1. Analysis and prediction of compromising electromagnetic radiation

   The subject of the doctoral dissertation is the use of statistical methods and digital signal processing to analyse and predict the electromagnetic radiation of electrical and electronic devices that could cause the leakage of secret information. On the basis of measurements using current or voltage probes on computer power cables, heating pipes or water pipes and other objects, time and frequency data are obtained. Using these data the analysis in time, frequency or other suitably designed area (bispectrum, trispectrum, cepstrum, etc.) is performed to verify whether it is possible to identify a compromising signal in the noise and perform its reconstruction to obtain information content. Based on the obtained database, machine learning and artificial neural networks will be use to design sophisticated procedures for preventing the leakage of secret information.

   Tutor: Smékal Zdeněk, prof. Ing., CSc.

2. Cybersecurity in Transport Systems

   The research will focus on the analysis of threats, vulnerabilities and security methods in Intelligent Transportation Systems (ITS), the Internet of Vehicles, inter-vehicle/intra-vehicle communication and associated digital systems and services in transportation. The work will further deal with how to secure these smart transport systems in an agile, robust and sustainable manner. The minor goal of the work is research of the protection of user privacy in ITS services. The participation on Department’s national and international research projects is expected.

   Tutor: Malina Lukáš, doc. Ing., Ph.D.

3. Methods for security testing of computer networks with IPv6 protocol

   The topic focuses on the research and design of new methods that can be used for security testing (including penetration testing) in networks in different phases of the transition to IPv6 (Internet Protocol version 6) protocols. The research focuses on methods applicable to testing network infrastructure, endpoint devices and other specialized devices, with an emphasis on so-called transition mechanisms.

   Tutor: Jeřábek Jan, doc. Ing., Ph.D.

4. Novel Methods of Visual Interpretation of Partial Results of Deep Learning Networks

   The theme is focused on a visualisation of partial results and features inside of classification processes used by deep learning networks. The goal is understanding of feature analysis and visual interpretation of partial processes namely for image data object classifiers. Produced methods should provide image outputs for both art and analytic utilisation. The goal in artistic field is image synthesis and analytic instruments are aimed to inner processes and partial stages mapping and analysis of their influence on results.

   Tutor: Říha Kamil, doc. Ing., Ph.D.

5. Post-Quantum Cryptographic Protocols

   The topic aims at the analysis, design and optimization of modern post-quantum cryptographic (PQC) protocols. The research can be more focused on the one of current open problems such as post-quantum security in blockchain technology, quantum-resistant privacy-preserving methods, PQC on constrained devices, quantum-resistant hybrid methods, etc. The participation on Department’s national and international research projects is expected.

   Tutor: Malina Lukáš, doc. Ing., Ph.D.

6. Reconstruction of degraded audio signals using combination of deep neural networks and model-based techniques

   The thesis will deal with modern approaches to audio signal restoration, specifically focusing on the task of filling in a missing gap in an audio signal and the related task of restoration of saturated samples. Problems of this type are commonly encountered in practice (archival recordings, dropouts in VoIP calls, etc.). Current methods provide a very good interpolation of signals that are stationary and harmonic in the vicinity of the corrupted segment. While current developments in the field of deep neural networks (DNN) are promising, DNNs have been shown to improve their performance when complemented with a physical formulation of the problem (model-based networks). The study will focus on approaches that combine algorithms that have been successful in recent years (optimization-based methods) and DNNs. The work will not neglect the psychoacoustic side of the problem. (Cooperation with the Acoustics Research Institute, Vienna)

   Tutor: Rajmic Pavel, prof. Mgr., Ph.D.

7. Research of novel methods of incomplete spatial information analysis in digital images

   The theme is focused on the research of novel methods for analysis of spatial information captured in digital images. These source data can be represented by temporal or spatial sequences eventually by a single image whereas the analysis should result from a given scene geometry.

   Tutor: Říha Kamil, doc. Ing., Ph.D.

1. round (applications submitted from 01.04.2024 to 30.04.2024)

1. Security and Privacy in Intelligent Infrastructures

   The topic focuses on the research of applied modern cryptography (light cryptography, schemes with privacy protection, authentication and key management) and optimization of schemes within intelligent networks such as Internet of Everything, Internet of vehicles and smart cities. The research deals in more detail with the design of secure decentralized and heteregenous networks and services with enhanced privacy protection of users. The participation on Department’s national and international research projects is expected.

   Tutor: Malina Lukáš, doc. Ing., Ph.D.

2. Using Machine Learning for Modelling of Audio Systems

   Neural networks and machine learning are currently used in the area of audio signal processing for data mining, e.g. recognition of genre, music information retrieval from recordings, etc., and speech processing, such as word recognition, speaker identification, emotion recognition, etc. However, their potential use is also in modelling of audio systems. The aim of dissertation thesis is to find algorithms for optimization of parameters of digital musical effects, algorithms for room acoustic simulation and more using machine learning and hearing models for training of neural networks. The research will focus on the static optimization of the system parameters according to the original analog system and on the dynamic change of the parameters in real time on the basis of the properties of the processed audio signal. Research will be conducted in collaboration with companies dealing with the development of software for processing audio signals.

   Tutor: Schimmel Jiří, doc. Ing., Ph.D.