Branch Details

Computer Science and Engineering

Original title in Czech: Výpočetní technika a informatikaFITAbbreviation: DVI4Acad. year: 2018/2019

Programme: Computer Science and Engineering

Length of Study: 4 years

Accredited from: 1.1.2007Accredited until: 31.12.2024

Profile

The goal of the doctoral study programme is to provide outstanding graduates from the MSc study programme with a specialised university education of the highest level in certain fields of information technology, including especially the areas of information systems, computer-based systems and computer networks, computer graphics and multimedia, and intelligent systems. The education obtained within this study programme also comprises a training and attestation for scientific work.

Supervisor

Issued topics of Doctoral Study Program

  1. Advanced Algorithms of Computer Graphics

    The topic focuses algorithms of computer graphics and generally computer image synthesis. Its main goal is to research algorithms so that their features and application possibilities are better understood, so that they are deeply analyzed, so that they are improved or newly created. The programming work is expected in C, C++, C#, assembly language, CUDA, OpenCl, VHDL, or other languages. If suitable, they can be efficiently implemented e.g. in CPU, in CPU with acceleration through SSE instructions, in embeded systems, in embedded systems with FPGA, or in other systems, such as x86/64, ARM, Xeon PHI, or other cores. Algorithms of interest include 3D model processing and acquisition. The algorithms of interest include:

    • rendering using selected computer graphics methods (such as ray tracing, photon mapping, direct rendering of "point clouds", etc.),
    • reconstruction of 3D scenes from images and/or video, eventually also fusing with other sensors, such as LIDAR,
    • new algorithms of graphics and image synthesis suitable for mobile and embedded systems,
    • modern algorithms of geometry suitable for applications in cpmputer graphics and perhaps also 3D printing,
    • methods of video processing in the form of "cartoon", with false colours, with simulation of painterly techniques, etc., 
    • emerging algorithms of 3D synthesis, holography, wavelet transform, frequency transform, etc.

    After mutual agreement, individually selected algorithms can be considered as well as soon as they do belong to the general topic.


    Tutor: Zemčík Pavel, prof. Dr. Ing.

  2. Advanced Algorithms of Computer Graphics

    The topic focuses algorithms of computer graphics and generally computer image synthesis. Its main goal is to research algorithms so that their features and application possibilities are better understood, so that they are deeply analyzed, so that they are improved or newly created. The programming work is expected in C, C++, C#, assembly language, CUDA, OpenCl, VHDL, or other languages. If suitable, they can be efficiently implemented e.g. in CPU, in CPU with acceleration through SSE instructions, in embeded systems, in embedded systems with FPGA, or in other systems, such as x86/64, ARM, Xeon PHI, or other cores. Algorithms of interest include 3D model processing and acquisition. The algorithms of interest include:

    • rendering using selected computer graphics methods (such as ray tracing, photon mapping, direct rendering of "point clouds", etc.),
    • reconstruction of 3D scenes from images and/or video, eventually also fusing with other sensors, such as LIDAR,
    • new algorithms of graphics and image synthesis suitable for mobile and embedded systems,
    • modern algorithms of geometry suitable for applications in cpmputer graphics and perhaps also 3D printing,
    • methods of video processing in the form of "cartoon", with false colours, with simulation of painterly techniques, etc., 
    • emerging algorithms of 3D synthesis, holography, wavelet transform, frequency transform, etc.

    After mutual agreement, individually selected algorithms can be considered as well as soon as they do belong to the general topic.


    Tutor: Zemčík Pavel, prof. Dr. Ing.

  3. Advanced Algorithms of Computer Graphics

    The topic focuses algorithms of computer graphics and generally computer image synthesis. Its main goal is to research algorithms so that their features and application possibilities are better understood, so that they are deeply analyzed, so that they are improved or newly created. The programming work is expected in C, C++, C#, assembly language, CUDA, OpenCl, VHDL, or other languages. If suitable, they can be efficiently implemented e.g. in CPU, in CPU with acceleration through SSE instructions, in embeded systems, in embedded systems with FPGA, or in other systems, such as x86/64, ARM, Xeon PHI, or other cores. Algorithms of interest include 3D model processing and acquisition. The algorithms of interest include:

    • rendering using selected computer graphics methods (such as ray tracing, photon mapping, direct rendering of "point clouds", etc.),
    • reconstruction of 3D scenes from images and/or video, eventually also fusing with other sensors, such as LIDAR,
    • new algorithms of graphics and image synthesis suitable for mobile and embedded systems,
    • modern algorithms of geometry suitable for applications in cpmputer graphics and perhaps also 3D printing,
    • methods of video processing in the form of "cartoon", with false colours, with simulation of painterly techniques, etc., 
    • emerging algorithms of 3D synthesis, holography, wavelet transform, frequency transform, etc.

    After mutual agreement, individually selected algorithms can be considered as well as soon as they do belong to the general topic.


    Tutor: Zemčík Pavel, prof. Dr. Ing.

  4. Advanced approaches in cellular automata design

    Tutor: Sekanina Lukáš, prof. Ing., Ph.D.

  5. Advanced genetic programming techniques

    Tutor: Sekanina Lukáš, prof. Ing., Ph.D.

  6. Advanced methods for monitoring and analysis of mobile communication

    Tutor: Matoušek Petr, Ing., Ph.D.

  7. Advanced methods for security analyses of event logs

    Tutor: Matoušek Petr, Ing., Ph.D.

  8. Advanced Methods of Computational Photography

    The project is concerned with advanced methods of computational photography. The aim is to research new computational photography methods, which comprises software solutions potentially supported by new optics and/or hardware. Our interest is on HDR image and video processing, color-to-grayscale conversions, spectral imaging, and others.

    • Further information: http://cadik.posvete.cz/tmo/
    • Contact: http://cadik.posvete.cz/
    • Cooperation and research visits with leading research labs are possible (Adobe Research, USA, MPII Saarbrücken, Germany, Disney Research Zurich, Switzerland, INRIA Bordeaux, France)

    Tutor: Čadík Martin, doc. Ing., Ph.D.

  9. Advanced methods of practicel reasoning in the BDI systems.

    Tutor: Zbořil František, doc. Ing., Ph.D.

  10. Advanced Rendering Methods

    The project is concerned with advanced rendering and global illumination methods. The aim is to research new photorealistic (physically accurate) as well as non-photorealistic (NPR) simulations of interaction of light with the 3D scene. Cooperation and research visits with leading research labs are possible (Adobe, USA, MPII Saarbrücken, Německo, Disney Curych, Švýcarsko, INRIA Bordeaux, Francie).

    Tutor: Čadík Martin, doc. Ing., Ph.D.

  11. Advancing cryptanalytic methods through soft-computing techniques

    Tutor: Vašíček Zdeněk, doc. Ing., Ph.D.

  12. Analysis of Anonymisation Networks Security

    Tutor: Hanáček Petr, doc. Dr. Ing.

  13. Analysis of Attacks on Wireless Networks

    Tutor: Hanáček Petr, doc. Dr. Ing.

  14. Approximate computing in low-power video processing

    Tutor: Vašíček Zdeněk, doc. Ing., Ph.D.

  15. Augmented Reality for Complex Real Time Simulation Environment

    Tutor: Chudý Peter, doc. Ing., Ph.D., MBA

  16. Augmented Reality on Mobile Devices

    The goal of the work is to research and create algorithms that will allow for running augmented reality on mobile (ultramobile) devices. It mainly concerns algorithms of pose estimation in the space by the means of computer vision and by using sensors embedded in the device. Furthermore, the work will elaborate on algorithms of rendering of virtual elements into the real-world scene and on applications of augmented reality on mobile devices.

    Tutor: Herout Adam, prof. Ing., Ph.D.

  17. Automated Dynamic Analysis, Intelligent Testing, and Software Quality Assurance

    Tutor: Vojnar Tomáš, prof. Ing., Ph.D.

  18. Automatic Desing of Ultrasound Treatment Plans

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

  19. Automatic Workload Balancing on Heterogeneous Architectures

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

  20. Automatized Definition of Context-Sensitive Grammars

    Tutor: Kolář Dušan, doc. Dr. Ing.

  21. Autonomous Inelligent Systems Driven by a Models

    Tutor: Zbořil František, doc. Ing., Ph.D.

  22. Bayseian networks - constructions and applications

    Tutor: Zbořil František, doc. Ing., CSc.

  23. Big Data Analysis by means of Deep Neural Networks

    Tutor: Smrž Pavel, doc. RNDr., Ph.D.

  24. Communication Infrastructure for Intelligent Buildings or Vehicles

    Tutor: Hanáček Petr, doc. Dr. Ing.

  25. Communication Monitoring Based on Device Profiles

    Device profile is characteristics of a device that is created by monitoring of running processes on a device and network communication of the device. The profile includes statistics and metadata about the device behaviour in active or passive state.

    Knowing device profiles helps network administrators and users to know how device communicates without explicit user interaction, e.g., during user data synchronization in cloud, software updates, application data synchronization (emails, calendar), etc. Knowledge of the device profile can be used to identify different types of network attacks, malware contagion, or unauthorized access and process running.

    The research will include selection of device profile data, implementation of the tool for retrieving such data, device profiling and identification of deviations in network communcation using clustering or automated filtering.

    This topic is a part of research project Integrated Platform for Analysis of Digital Data from Security Incidents (Tarzan).

    Tutor: Matoušek Petr, Ing., Ph.D.

  26. Communication Protocol for Cockpit Display Systems and User Applications data exchange in Avionics Systems

    Tutor: Chudý Peter, doc. Ing., Ph.D., MBA

  27. Computer Vision in Traffic Monitoring

    • Research and development of computer vision algorithms.
    • Focus on videos from traffic surveillance cameras.
    • Research of algorithms avoiding user input.
    • Collection and synthesis of suitable data sets.
    • Implementation of experimental prototypes.
    • Design and prototyping of applications.

    Tutor: Herout Adam, prof. Ing., Ph.D.

  28. Concept of algorithms for removal of influence of skin diseases on the process for fingerprint recognition

    Tutor: Drahanský Martin, prof. Ing., Ph.D.

  29. Dependability Issues of Operating Systems and Applications They Control

    Modern operating systems (OS) must meet many requirements not only in terms of flexibility and efficiency of their execution on recent computing platforms, but also in terms of dependability of their kernels and services they provide to the application layer. The aim of the project is:

    • to analyze the actual state in the area of dependability of OS kernels / services,
    • to identify (in terms of dependability) negative effects and their impact to dependability of the application layer,
    • to propose a method for increasing dependability of OS kernels / services,
    • to evaluate an impact of the method to dependability of OS kernels / services and operation of the application layer.

    The project can be oriented into various directions, such as low-power applications / OS or application / OS designed to run in an embedded or a multi-core environment. During the project, a "conventional" OS such as Unix, Linux, Android, Windows, iOS or a specialized OS such as QNX, uC/OS-I (II, III), FreeRTOS, MQX can be utilized.

    Tutor: Strnadel Josef, Ing., Ph.D.

  30. Design Techniques for Multifunctional Logic Circuits

    Tutor: Růžička Richard, doc. Ing., Ph.D., MBA

  31. Detection and localization of (living) people behind obstacles

    Tutor: Drahanský Martin, prof. Ing., Ph.D.

  32. Detection and Re-Identification of Objects in Image and Video

    • Omnidirectional object detection in real time
    • Re-identification of detected objects, e.g. in shots from different cameras or at different points in time
    • Focused on statinary surveillance cameras
    • Focused on automatic traffic surveillance

    Tutor: Herout Adam, prof. Ing., Ph.D.

  33. Distributed Control Systems and IoT Based on Reconfigurable Petri Nets

    Tutor: Janoušek Vladimír, doc. Ing., Ph.D.

  34. Efficient Automata and Logic Technology (Not Only) for Formal Analysis and Verification

    Tutor: Vojnar Tomáš, prof. Ing., Ph.D.

  35. Embedded video/signal processing

    The topic focuses embedded image, video and/or signal processing. Its main goal is to research capabilities of "smart" and "small" units that have such features that allow for their applications requiring smyll, hidden, distributed, low power, mechanically or climatically stressed systems suitable of processing of some signal input. Exploitation of such systems is perspective and wide and also client/server and/or cloud systems. The units themselves can be based on CPU/DSP/GPU, programmable hardware, or their combination. Smart cameras can be considered as well. Applications of interest include:

    • classification of images or objects using machine learning (AI)using traditional methods or through deep convolution networks neural network or similar approaches (e.g. for industrial quality inspection, etc.),
    • parallel analysis of signal(s) and video (e.g. for robust detection of occurrence of object in industrial or surveillance applications),
    • modern algorithms of video, image, and/or signal exploiting "client/server" or "cloud" (with focus on the technlogy) suitable e.g. for mobile technology and/or embedded systems,
    • other similar topics can be individually consulted and considered.

    A possibility exists in collaboration on grant projects, especially the newly submitted TAČR, H2020, ECSEL ones (potentially employment or scholarship possible).

    Tutor: Zemčík Pavel, prof. Dr. Ing.

  36. Environment for Modeling and Optimization Software Engineering Processes

    Tutor: Kreslíková Jitka, doc. RNDr., CSc.

  37. Exploitation of Machine Learning for Exact Classification of Malware

    Tutor: Kolář Dušan, doc. Dr. Ing.

  38. Forensic image processing from mobile devices

    Tutor: Drahanský Martin, prof. Ing., Ph.D.

  39. Formal Models of Distributed Computation

    Tutor: Meduna Alexandr, prof. RNDr., CSc.

  40. General Purpose GPU

    Tutor: Smrž Pavel, doc. RNDr., Ph.D.

  41. High-Level Petri Nets in Embedded systems and IoT Architectures

    Tutor: Janoušek Vladimír, doc. Ing., Ph.D.

  42. Human-Robot Interaction in Collaborative Environment

    Tutor: Beran Vítězslav, Ing., Ph.D.

  43. Hybrid Reprogrammable Processing Platforms

    Tutor: Fučík Otto, doc. Dr. Ing.

  44. Image and video quality assessment metrics

    The project deals with image and video quality assessment metrics (IQM). The aim is to explore new ways how to incorporate human visual system properties into IQM. In particular, we will consider perception of HDR images, and utilization of additional knowledge (in form of metadata, 3D information, etc.) about the tested scenes using machine learning (e.g. neural networks).

    Tutor: Čadík Martin, doc. Ing., Ph.D.

  45. Image Processing using Neural Networks

    The project is concerned with advanced methods of image processing. The aim is to research new methods using machine learning, in particular deep convolutional neural networks.

    • Contact: http://cadik.posvete.cz/
    • Cooperation and research visits with leading research labs are possible (Adobe Research, USA, MPII Saarbrücken, Germany, Disney Research Zurich, Switzerland, INRIA Bordeaux, France)

    Tutor: Čadík Martin, doc. Ing., Ph.D.

  46. Information Extraction from Wikipedia and Other Web Sources

    Tutor: Smrž Pavel, doc. RNDr., Ph.D.

  47. Information Technologies in Psychology

    Tutor: Smrž Pavel, doc. RNDr., Ph.D.

  48. Intelligent Inspection and Measuring of Cavities with a Cylindric Diameter and Prediction of the State Change

    Tutor: Drahanský Martin, prof. Ing., Ph.D.

  49. Intrusion Detection and Automatic Processing of Malware

    Tutor: Hanáček Petr, doc. Dr. Ing.

  50. Low-power deep learning on a chip

    Tutor: Sekanina Lukáš, prof. Ing., Ph.D.

  51. Machine Learning for Industry 4.0

    Tutor: Smrž Pavel, doc. RNDr., Ph.D.

  52. Modern and Accelerated Visal Computing Algorithms

    Tutor: Zemčík Pavel, prof. Dr. Ing.

  53. Modern Methods of Computer Vision

    • Use of modern and promising approaches to computer vision, especially methods of machine learning and convolutional neural networks
    • Identification of promising open problems
    • Design and development of non-traditional modifications of existing approaches
    • Experimental evaluation, use of existing data sets and collection of new ones

    Tutor: Herout Adam, prof. Ing., Ph.D.

  54. Modern Models for the Definition and Translation of Languages

    Tutor: Meduna Alexandr, prof. RNDr., CSc.

  55. Modern ways of communication with information systems

    Tutor: Hruška Tomáš, prof. Ing., CSc.

  56. Multispectral analysis of human tissues for medical purposes

    Tutor: Drahanský Martin, prof. Ing., Ph.D.

  57. New approaches to optimizations

    Tutor: Zbořil František, doc. Ing., CSc.

  58. New Versions of Automata and Grammars

    Tutor: Meduna Alexandr, prof. RNDr., CSc.

  59. Optimal Flight Trajectory and Pilot Decision Making

    Tutor: Chudý Peter, doc. Ing., Ph.D., MBA

  60. Optimisation Distributed Input-Output Operations

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

  61. Optimization of portofolio allocation cumulative risks

    Tutor: Kreslíková Jitka, doc. RNDr., CSc.

  62. Parallel Analysis of Context-Sensitive Languages

    Tutor: Kolář Dušan, doc. Dr. Ing.

  63. Parallel Analysis of Formal Languages

    Tutor: Kolář Dušan, doc. Dr. Ing.

  64. Phenomenological Modeling of Cyber-Physical Systems

    Tutor: Chudý Peter, doc. Ing., Ph.D., MBA

  65. Processing of Video, Image, and/or Signal

    The topic focuses algorithms of image, video, and/or signal processing. Its main goal is to research and in-depth analyze existing algorithms and discover new ones so that they have desirable features and so that they are possible to efficiently implement. Such efficient implementation can be but does not necessarily have to be part of the work but it is important to prepare the algorithms so that they can be efficiently implemented e.g. in CPU, in CPU with acceleration through SSE instructions, in embeded systems, in embedded systems with FPGA, in Intel Xeon PHI, in extremely low power systems, or in other environments. The programming work is expected in C, C++, C#, assembly language, CUDA, OpenCl, VHDL, or other languages. The application possibilities of the algorithms are also important and the application can be but does not have to be part of the work. The algorithms/applications of interest include:

    • recognition of scene contents, events, and general semantics of video sequences (such as identification of traffic situations, identification in scenes in moview, action identification, etc.),
    • classification of video sequences using machine learning (AI)through deep convolution networks neural network or similar approaches (e.g. for industrial quality inspection, object of scene characteristics search, etc.),
    • object tracking in video using modern methods (such as TLD or particle tracking)
    • parallel analysis of video and signal (e.g. for detection of coincidence of occurrence of object in video and characteristic signal shape in surveillance applications),
    • modern algorithms of video, image, and/or signal exploiting "client/server" or "cloud" approaches suitable e.g. for mobile technology and/or embedded systems,
    • algorithms of video compression and analysis through frequency or wavelet transforms or similar methods...

    After mutual agreement, individually selected algorithms can be considered as well as soon as they do belong to the general topic.

    Tutor: Zemčík Pavel, prof. Dr. Ing.

  66. Processing Platform for Embedded Intelligence

    Tutor: Fučík Otto, doc. Dr. Ing.

  67. Quality Management Model

    Tutor: Kreslíková Jitka, doc. RNDr., CSc.

  68. Real Robots Planning Algorithms

    Tutor: Zbořil František, doc. Ing., Ph.D.

  69. Recognition and Tracking of Human Body in Video

    • Study and research of algorithms of computer vision.
    • Focus on detection, recognition, and pose estimation of a human body.
    • Tracking of parts of human body in time, using temporal coherence.
    • Design and implementation of algorithms working in real time.

    Tutor: Herout Adam, prof. Ing., Ph.D.

  70. Rouhg Sets and Big Data

    Tutor: Zbořil František, doc. Ing., CSc.

  71. Safe Compilers

    Tutor: Kolář Dušan, doc. Dr. Ing.

  72. Security Monitoring of Industrial IoT and SCADA Networks

    SCADA (Supervisory Control And Data Acquisition) systems and industrial IoT networks provides control and monitoring of industrial processes and devices. In the past, SCADA communication was usually transmitted over dedicated data links with Token Ring or HDLC protocols. Today, SCADA and industrial IoT communication is transmitted over TCP/IP or connected to the Internet.

    This rises serious security concerns. DLMS/COSEM, IEC 104 or IEC 61850 communication is usually used for energy smart metering and control where security incidents are critical. One of the solution is to provide security monitoring of these protocols using extended flow network that can be used to detect security incidents.

    This dissertation will be focused on behavior of industrial IoT and SCADA  communication and detection of common threats (malformed packets, DoS attacks, forged commands, unauthorized data acquisition). The goal of the dissertation is to propose and verify new approaches for IoT network intrusion detection using flow monitoring and anomaly detection.

    This topic is a part of international research project IoT Monitoring and Forensics (IRONSTONE).

    Tutor: Matoušek Petr, Ing., Ph.D.

  73. Security monitoring of IoT Communication

    Internet of Thing is a communication platform that interconnects different types of home devices (home IoT networks) or industrial devices (industrial IoT networks). These devices usually lack sufficient protection against network attacks. Unfortunately, these attacks can cause serious demages.  Besides intentional attacks, also malfuctioning or failures can cause serious demages.

    Thus IoT monitoring becomes a new domain of network monitoring and management. It includes monitoring of device behaviour, monitoring data acquisition, device settings, etc. Security monitoring focuses on detection of attack and anomalies in communication. Traditional methods used in security monitoring have limited scope of usage because IoT communication differs from common communication patterns on Internet. Thus, it is necessary to extend these method or propose a new approach how to analyze IoT monitoring metadata.

    The goal of this disertation is to analyze different method of IoT security monitoring and define how to protect these network against common threats. This advanced monitoring system should be implemented into existing SIEM systems.

    This topic is a part of international research IoT Monitoring and Forensics (IRONSTONE) by TACR.

    Tutor: Matoušek Petr, Ing., Ph.D.

  74. Speech data mining

    The proposed dissertation deals with a subset of techniques for extracting meaningful information from speech: voice activity detection, transcription, keyword spotting, speaker recognition, language recognition and other possible modalities. It includes investigation into relevant signal processing and machine learning, and experimentation on standard speech data-sets. The topic is related to several projects running in the BUT Speech@FIT group, see http://speech.fit.vutbr.cz/projects. The candidate should have strong background in mathematics, linear algebra and statistics, and experience in one or more of the following disciplines: signal processing, speech signal processing, machine learning, natural language processing, data-mining. He/she should be experienced with usual scientific programming and scripting languages (C, Matlab, Python). Experience with at least one of machine learning/speech toolkits (Theano, Keras, PyTorch, CNTK, Chainer, KALDI, HTK) is a plus. As the the group is international, a good working knowledge of English is required. 

    Tutor: Černocký Jan, doc. Dr. Ing.

  75. Static Formal Analysis of Programs with Advanced Data and Control Structures

    Tutor: Vojnar Tomáš, prof. Ing., Ph.D.

  76. Synthesis of Stochastic Models

    Tutor: Vojnar Tomáš, prof. Ing., Ph.D.

  77. Systems based on regulated automata and grammars

    Tutor: Meduna Alexandr, prof. RNDr., CSc.

  78. Task Based Parallelism on Heterogeneous Architectures

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

  79. Testing Methods for Security Products

    Tutor: Hanáček Petr, doc. Dr. Ing.

  80. The design of fault tolerant systems reflecting low power

    Tutor: Kotásek Zdeněk, doc. Ing., CSc.

  81. The possibilities of using time redundancy during the design of fault tolerant systems

    Tutor: Kotásek Zdeněk, doc. Ing., CSc.

  82. Transformation of Models for Formal Languages

    Tutor: Meduna Alexandr, prof. RNDr., CSc.

  83. Unconventional Modeling and Analysis of Fault-Tolerant Systems


    Recent systems are becoming more and more demanding not only from the viewpoints of flexibility and efficiency of their operation on modern computing platforms, but also from the viewpoint of their activities and the services they provide and how they are managed.
    The aim of the project is:

    • to analyze the actual state in the area of modeling and analysis of fault tolerant systems and assessment of their dependability dependability attributes, to identify problems and limitations of conventional methods and to propose their solutions,
    • to choose, under conditions that make it difficult or impossible for conventional means and methods, unconventional means and methods for modeling and analysis of fault-tolerant systems and for assessment of their dependability attributes and their failure effects,
    • to propose a solution of increasing dependability for the selected class of systems, and to verify such a solution using  proper case studies,
    • to evaluate an impact of the proposed solution to dependability, to analyze its properties, and to compare it with existing approaches.

    By default, it is assumed that the project will be oriented to digital electronic systems; however, the subject can be further oriented / specialized, for example into the areas of processor and/or FPGA based systems, reconfigurable devices, cyber-physical systems, dependability of hardware, firmware, application and operating system layers etc.

    Tutor: Strnadel Josef, Ing., Ph.D.

  84. Use of Non-Reproducible Properties of Electronic Systems to Increase Security


    Modern systems must meet many requirements not only in terms of flexibility and efficiency of their execution on recent computing platforms, but also in terms of security. The aim of the project is:

    • To analyze and document the causes of the production variability of electronic circuit parameters designed and manufactured under identical conditions, to document typical problems associated with the production variability and their solutions.
    • To choose a set of physical samples of a specific electronic circuit (e.g., a microcontroller or an FPGA) for appropriate, experimental based validation, demonstration and documentation of the production variability of their parameters.
    • Based on the experimental results, to propose a method of practical application of the variability, e.g. to realize a physically unclonable function,  physically unclonable identification of samples, non-reproducible random number generation or non-reproducible encryption of a communication channel.
    • To verify properties of the proposed methods for a sufficiently large number of samples, to summarize the properties, to discuss the achieved results and, potentially, to propose improvements of the methods based on further sources of inaccuracy.
    The theme of the project is very promising both from the scientific and publishing viewpoints and, especially, from the viewpoint of the practical, or even revolutionary, contribution in the security area.

    Tutor: Strnadel Josef, Ing., Ph.D.

  85. User Experience and Modern User Interfaces

    • Study and design of advanced web and mobile user interfaces.
    • Validation, optimization, and user testing of web and mobile user interfaces.
    • Statistical processing of data collected from human respondents / users.
    • Design, development, and deployment of practically usable web/mobile system / user interface.

    Tutor: Herout Adam, prof. Ing., Ph.D.

  86. Tutor: Burget Radek, Ing., Ph.D.

  87. Tutor: Burget Radek, Ing., Ph.D.

  88. Tutor: Janoušek Vladimír, doc. Ing., Ph.D.

  89. Tutor: Janoušek Vladimír, doc. Ing., Ph.D.

  90. Tutor: Kotásek Zdeněk, doc. Ing., CSc.

  91. Tutor: Růžička Richard, doc. Ing., Ph.D., MBA

  92. Tutor: Zbořil František, doc. Ing., CSc.


Course structure diagram with ECTS credits

2. year of study, winter semester
AbbreviationTitleL.Cr.Com.Compl.Hod. rozsahGr.Op.
JADPh.D. Test of Englishcs, en0CompulsoryDrExyes
2. year of study, summer semester
AbbreviationTitleL.Cr.Com.Compl.Hod. rozsahGr.Op.
JADPh.D. Test of Englishcs, en0CompulsoryDrExyes
Any year of study, winter semester
AbbreviationTitleL.Cr.Com.Compl.Hod. rozsahGr.Op.
JA6DEnglish for PhD Studentscs, en0OptionalDrExP - 13 / COZ - 13yes
PDDApplications of Parallel Computerscs, en0OptionalDrExP - 39yes
IV108Bioinformaticscs, en0OptionalDrExP - 13 / COZ - 13yes
FADFormal Program Analysiscs, en0OptionalDrExP - 26yes
MSDModelling and Simulationcs, en0OptionalDrExP - 39 / Cp - 9yes
MMDAdvanced Methods of 3D Scene Visualisationcs, en0OptionalDrExP - 39yes
MZDModern Methods of Speech Processingcs, en0OptionalDrExP - 39yes
TIDModern Theoretical Computer Sciencecs, en0OptionalDrExP - 39 / PR - 13yes
OPDOpticscs, en0OptionalDrExP - 39 / PR - 13yes
ORIDOptimal Control and Identificationcs, en0OptionalDrExP - 26 / PR - 13yes
PGDComputer Graphicscs, en0OptionalDrExP - 39yes
PBDAdvanced Biometric Systemscs, en0OptionalDrExP - 26 / PR - 4yes
PNDAdvanced Techniques in Digital Designcs, en0OptionalDrExP - 39yes
PTDThe Principles of Testable Design Synthesiscs, en0OptionalDrExP - 39yes
DMA1Statistics, Stochastic Processes, Operations Researchcs0OptionalDrExS - 39yes
TKDCategory Theorycs, en0OptionalDrExP - 26yes
TJDProgramming Language Theorycs, en0OptionalDrExP - 39yes
APDSelected Topics on Language Parsing and Translationcs, en0OptionalDrExP - 39 / PR - 13yes
ZZDKnowledge Discovery in Databasescs, en0OptionalDrExP - 39 / PR - 13yes
DBM1Advanced Methods of Processing and Analysis of Imagescs0OptionalDrExP - 39yes
ZPDNatural Language Processingcs, en0OptionalDrExP - 39yes
ASDAudio and Speech Processing by Humans and Machinescs, en0OptionalDrExP - 39yes
Any year of study, summer semester
AbbreviationTitleL.Cr.Com.Compl.Hod. rozsahGr.Op.
JA6DEnglish for PhD Studentscs, en0OptionalDrExP - 13 / COZ - 13no
BIDInformation System Security and Cryptographycs, en0OptionalDrExP - 39 / PR - 4yes
EUDEvolutionary and Unconventional Hardwarecs, en0OptionalDrExP - 26yes
EVDEvolutionary Computationcs, en0OptionalDrExP - 39yes
ISDIntelligent Systemscs, en0OptionalDrExP - 26 / PR - 26yes
KRDClassification and recognitioncs, en0OptionalDrExP - 39yes
MLDMathematical Logiccs, en0OptionalDrExP - 26yes
MIDModern Mathematical Methods in Informaticscs, en0OptionalDrExP - 26yes
QB4Neural Networks, Adaptive and Optimum Filteringcs, en0OptionalDrExP - 39yes
SODFault Tolerant Systemscs, en0OptionalDrExP - 39yes
TADTheory and Applications of Petri Netscs, en0OptionalDrExP - 39 / Cp - 8yes
PFTDTheory of Financial Marketscs, en0OptionalDrExP - 26 / COZ - 20yes
VKDSelected Chapters on Algorithmscs, en0OptionalDrExP - 39yes
VPDSelected Topics of Information Systemscs, en0OptionalDrExP - 39yes
SIDSelected Topics of Software Engineering and Database Systemscs, en0OptionalDrExP - 39 / PR - 13yes
VNDHigly Sophisticated Computationscs, en0OptionalDrExP - 39 / Cp - 26yes