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.

prof. RNDr. Milan Češka, CSc.

1. Accelerated Visal Computing Algorithms

   Tutor: Zemčík Pavel, prof. Dr. Ing.

2. Adaptive Policies for Distributed Applications in RINA

   Tutor: Kolář Dušan, doc. Dr. Ing.

3. Adaptive Policies for Distributed Applications in RINA

   .

   Tutor: Kolář Dušan, doc. 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 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.

7. 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.

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

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

9. Advanced optimization of logic circuits

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

10. Advanced optimization of logic circuits

    .

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

11. Advanced optimization of logic circuits

    Ukazuje se, že metody syntézy číslicových obvodů využívající evolučních algoritmů, zejména kartézského genetického programování pracujícího přímo nad reprezentací na úrovni hradel, jsou schopny produkovat implementace, které jsou v řadě případů mnohem efektivnější (typicky kompaktnější) nežli implementace získané pomocí současných syntézních technik využívajících interní reprezentace (např. AIG) a iterativní aplikace deterministických přepisovacích pravidel. Typickým cílem optimalizace je redukovat počet hradel optimalizovaného obvodu. V praxi se však vyskytuje požadavek optimalizovat obvod z hlediska více kriterií (např. zpoždění, plocha na čipu). V případě využití systému pro účely resyntézy je multikriteriální optimalizace nutností z důvodu zachování zpoždění obvodu, jehož část je předmětem optimalizace. 
    
    Cílem disertační práce je navázat na předchozí výzkum a zabývat se možnostmi multikriteriální optimalizace číslicových obvodů s ohledem na dobrou škálovatelnost. Dále se předpokládá využití alternativních reprezentací jako je např. majority uzel, které lépe odrážejí principy nových technologií.
    
    Výzkum spadá do témat řešených výzkumnou skupinou Evolvable Hardware.

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

12. 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).
    
    

    • More information: http://cadik.posvete.cz/

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

13. 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).
    
    

    • More information: http://cadik.posvete.cz/

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

14. Advancing cryptanalytic methods through soft-computing techniques

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

15. Analysis of Anonymisation Networks Security

    Tutor: Hanáček Petr, doc. Dr. Ing.

16. Analysis of Attacks on Wireless Networks

    Tutor: Hanáček Petr, doc. Dr. Ing.

17. Analysis of retinal images to refine the diagnosis and prognosis of disease progression

    The aim of the thesis is to design and implement an application for more accurate diagnosis and prognosis of disease progression. Specifically, it will be:
    

    • Study the way to capture the eye retina images and diseases that occur on the retina of the eye.
    • Design and implementation of algorithm for detection and localization of pathological findings in retinal images.
    • Designing and implementing an algorithm for comparing retinal images with each other to verify that images are coming from the same eye of the same patient, and to detect changes in disease progression.
    • Implementation of experiments and evaluation of achieved results.
    Participation on major international conferences and publishing in scientific or scientific journals is expected. Foreign internship is possible, even strongly supported. The cooperation will include cooperation with the ophthalmological departments of the Faculty Hospital at St. Anne in Brno and the University Hospital Brno.

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

18. Anonymization networks

    .

    Tutor: Ryšavý Ondřej, doc. Ing., Ph.D.

19. Anonymization networks

    Tutor: Ryšavý Ondřej, doc. Ing., Ph.D.

20. Application of models and their transformation in the process of developing and deploying systems

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

21. Approximate computing in machine learning

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

22. Artificial intelliegence for MindSphere

    The aim of the thesis is to create artificial intelligence for the MindSphere environment of Siemens, namely:
    

    • Familiarize yourself with MindSphere from Siemens and IoT.
    • Identify the IoT area and gain data in this area as part of communication with Siemens.
    • Design and implementation of the MindSphere learning and decision algorithm in the selected IoT area.
    • Implementation of experiments and summary of achieved results.
    Participation in major international conferences and publishing in scientific or scientific journals is expected. Foreign internship is possible and strongly supported. This work will be solved in cooperation with Siemens. There is the possibility of an extraordinary scholarship from Siemens.

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

23. Artificial intelliegence for MindSphere

    The aim of the thesis is to create artificial intelligence for the MindSphere environment of Siemens, namely:
    

    • Familiarize yourself with MindSphere from Siemens and IoT.
    • Identify the IoT area and gain data in this area as part of communication with Siemens.
    • Design and implementation of the MindSphere learning and decision algorithm in the selected IoT area.
    • Implementation of experiments and summary of achieved results.
    Participation in major international conferences and publishing in scientific or scientific journals is expected. Foreign internship is possible and strongly supported. This work will be solved in cooperation with Siemens. There is the possibility of an extraordinary scholarship from Siemens.

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

24. Automated Complexity Analysis of programs with (not only) Complex Data Structures

    Tutor: Rogalewicz Adam, doc. Mgr., Ph.D.

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

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

26. Automatic Protocol Reverse Engineering

    Tutor: Ryšavý Ondřej, doc. Ing., Ph.D.

27. Automatic speech processing for security applications

    
    Considerable part of the BUT Speech@FIT group activities is linked to speech data mining in security, intelligence and defense applications. 
    The topic of this dissertation if research in the areas of: 
    

    • speech recognition 
    • detection of keywords and key-phrases. 
    • speaker recognition 
    • language recognition 
    with regard to real speech signals (spontaneous speech, noise, distortions, channel variability). 

    Tutor: Černocký Jan, doc. Dr. Ing.

28. Automatic speech processing for security applications

    
    Considerable part of the BUT Speech@FIT group activities is linked to speech data mining in security, intelligence and defense applications. 
    The topic of this dissertation if research in the areas of: 
    

    • speech recognition 
    • detection of keywords and key-phrases. 
    • speaker recognition 
    • language recognition 
    with regard to real speech signals (spontaneous speech, noise, distortions, channel variability). 

    Tutor: Černocký Jan, doc. Dr. Ing.

29. Automatic speech processing for security applications

    
    Considerable part of the BUT Speech@FIT group activities is linked to speech data mining in security, intelligence and defense applications. 
    The topic of this dissertation if research in the areas of: 
    

    • speech recognition 
    • detection of keywords and key-phrases. 
    • speaker recognition 
    • language recognition 
    with regard to real speech signals (spontaneous speech, noise, distortions, channel variability). 

    Tutor: Černocký Jan, doc. Dr. Ing.

30. Automatic speech processing for security applications

    
    Considerable part of the BUT Speech@FIT group activities is linked to speech data mining in security, intelligence and defense applications. 
    The topic of this dissertation if research in the areas of: 
    

    • speech recognition 
    • detection of keywords and key-phrases. 
    • speaker recognition 
    • language recognition 
    with regard to real speech signals (spontaneous speech, noise, distortions, channel variability). 

    Tutor: Černocký Jan, doc. Dr. Ing.

31. Automatic Workload Balancing on Heterogeneous Architectures

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

32. Autonomous Inelligent Systems Driven by a Models

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

33. Big Data Analysis by means of Deep Neural Networks

    .

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

34. Big Data Analysis by means of Deep Neural Networks

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

35. Big Data Analysis by means of Deep Neural Networks

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

36. Big Data Analysis by means of Deep Neural Networks

    .

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

37. Communication Infrastructure for Intelligent Buildings or Vehicles

    Tutor: Hanáček Petr, doc. Dr. Ing.

38. 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.

39. Create a 3D model of head from 2D photos of diverse origins

    The aim of the thesis is to create 3D face model from 2D photos of diverse origins, namely:
    

    • Getting acquainted with creating a 3D model from 2D photos.
    • Specify options - photo size and resolution, photo age, head position, B & W / color photography, and other parameters to create a 3D model from this data.
    • Design and implementation of the algorithm for determining the parameters from the previous point to determine the usability of the input data and enable the creation of a 3D model.
    • Design and implementation of a 3D model creation algorithm from usable input data.
    • Implementation of experiments and summary of achieved results.
    Participation on major international conferences and publishing in scientific or scientific journals is expected. Foreign internship is possible and strongly supported. This thesis will be dealt with in cooperation with the Police of the Czech Republic.

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

40. Dependability Issues of Systems Driven by Operating Systems

    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.

41. Design Techniques for Multifunctional Logic Circuits

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

42. 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.

43. Detection of cyber attacks against critical infrastructure networks

    Communication networks of critical infrastructure includes smart grid networks whose blackout can have enormous effect on industry or life of people. A major task of cyber security is to detect attacks against control communication of critical infrastructure in order to provide its robustness and reliability.
    
    The research topic will be focused on automated monitoring of smart grid ICS (Industrial Control System) communication, providing of ICS visibility, and advanced processing of monitoring data in order to prevent cyber threats. Various techniques commonly used in IT networks will be applied in OT (Operation Technology) environment.
    
    The goal of the research is to describe typical patterns of cyber attacks against critical infrastructure and propose methods and procedures how to identify and detect such attacks. The result will be evaluted on data from project partners.
    
    The topic will be a part of National Competence Centre for Cybersecurity.
    

    Tutor: Matoušek Petr, Ing., Ph.D.

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

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

45. Dynamic Reconfiguration in Computer Networks

    .

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

46. Dynamic Reconfiguration in Computer Networks

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

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

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

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

    .

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

49. Embedded Systems for Video/Signal

    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.

50. Encrypted traffic monitoring

    Tutor: Ryšavý Ondřej, doc. Ing., Ph.D.

51. Environment for Modeling and Optimization Software Engineering Processes

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

52. Factory driven by sociable intelligent agents and actors

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

53. Forensic image processing from mobile devices

    The aim of the thesis is to analyze photographs and video sequences from mobile devices, consisting of:
    

    • Getting familiar with all possible ways of recording on mobile devices, including various chips and optics.
    • Analyzing the data to determine the sensor type and optics only based on image information, including the ability to compare images from the same source.
    • Design and implementation of the application to the above stated point.
    • Implementation of experiments and summary of achieved results.
    Participation on major international conferences and publishing in scientific or scientific journals is expected. Foreign internship is possible and strongly supported. This thesis will be dealt in cooperation with the Police of the Czech Republic.

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

54. Forensic image processing from mobile devices

    The aim of the thesis is to analyze photographs and video sequences from mobile devices, consisting of:
    

    • Getting familiar with all possible ways of recording on mobile devices, including various chips and optics.
    • Analyzing the data to determine the sensor type and optics only based on image information, including the ability to compare images from the same source.
    • Design and implementation of the application to the above stated point.
    • Implementation of experiments and summary of achieved results.
    Participation on major international conferences and publishing in scientific or scientific journals is expected. Foreign internship is possible and strongly supported. This thesis will be dealt in cooperation with the Police of the Czech Republic.

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

55. Formal Models of Parallel Computation

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

56. General Purpose GPU

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

57. Generate damage to synthetic fingerprints and analyze their quality

    The aim of this work is to generate various damages into synthetic fingerprints and analysis of their quality. The work will consist of:
    

    • Familiarization with biometric fingerprint recognition, synthetic fingerprint generators, various damages in fingerprints and fingerprint quality estimation methods.
    • Design and implementation of algorithms for inserting (simulating) different types of damage into synthetic fingerprints.
    • Design and implementation of methods for fingerprint quality estimation, ideally combined with existing methods.
    • Realization of experiments and summary of achieved results.
    Participation on major international conferences and publishing in scientific or scientific journals is expected. Foreign internship is possible and strongly supported. This thesis will be dealt with in cooperation with the Police of the Czech Republic.

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

58. Hardware Trojans Protection Using Polymorphic Electronics

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

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

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

60. Human-Robot Interaction in Collaborative Environment

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

61. Hybrid Reprogrammable Processing Platforms

    Tutor: Fučík Otto, doc. Dr. Ing.

62. 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).
    

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

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

63. 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.

64. Information Extraction from the WWW

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

65. Information Extraction from Wikipedia and Other Web Sources

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

66. Intelligent inspection and measurement of cylindrical cross section cavities with prediction of state changes

    The aim of this dissertation is to design and implement software for evaluation of measured data of cylindrical cavities. Based on the measured data, the application creates a computer model of the cavity in which it will look for damaged or otherwise problematic sites. The system will be able to predict the development of this site in the future under the same conditions of use of a device containing a measured cylindrical cavity (e.g. a barrel of military weapons). The device is available + can be fitted with other sensors as required. Research can be divided into the following stages:
    

    • Study of the cavity scanning theory of the cylindrical cross section (specifically the main military techniques).
    • Designing methods for capturing and retrieving data.
    • Design and implementation of an algorithm to generate a computer model based on measured data.
    • Design and implementation of an algorithm for computer model analysis and automatic evaluation of the damaged surface or problem site.
    • Design and implementation of an intelligent algorithm to predict the further development of a damaged surface or problem site based on the history of the measured data.
    • Implementation of experiments and evaluation of achieved results.
    Participation in major international conferences and publishing in scientific or scientific journals is expected. Foreign internship is possible and is strongly supported. Collaboration will be in the field of military technology with relevant partners.

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

67. Intrusion Detection and Automatic Processing of Malware

    Tutor: Hanáček Petr, doc. Dr. Ing.

68. IoT Processor Design

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

69. Large scale solver of Maxwell equations using the k-Wave toobox

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

70. Low-power deep learning on a chip

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

71. Machine Learning for Industry 4.0

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

72. Machine Learning for Industry 4.0

    .

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

73. Machine Learning for Industry 4.0

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

74. Machine learning for processes based on actors

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

75. Methods for Pattern Extraction and Detection in Program Code

    Tutor: Kolář Dušan, doc. Dr. Ing.

76. Mobile Technology and Wearable Electronics for Analysis of Mental Health and Well-being

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

77. Mobile Technology and Wearable Electronics for Analysis of Mental Health and Well-being

    .

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

78. Modeling and validation of requirements in the process of developing software systems

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

79. 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.

80. Modern Models for the Transformation of Languages

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

81. Modern Models for the Transformation of Languages

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

82. Modern Models for the Transformation of Languages

    .

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

83. Modern ways of communication with information systems

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

84. Neural Representations in Multi-lingual Speech Modeling

    
    Current deep machine learning methods are based on continuous vector representations that are created by the neural networks (NN) themselves during the training. Although empirically, the results of NNs are often excellent, our
    knowledge and understanding of such representations is insufficient. The task for this dissertation is to study neural representations for speech and text units of different scopes (from phonemes and letters to whole spoken and written documents) and representations acquired both for isolated tasks and multi-task setups: 
    

    • Systematic study of neural structures for speech and text modeling in multi-modal and multilingual settings.
    • Addressing hierarchy of neural representations, human interpretability, and training under realistic conditions of non-ideal and incoherent data.

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

85. New Algorithms of Computer Graphics

    The topic concerns algorithms of computer graphics and image synthesis. Its main goal is to research new algorithms so that their features and application possibilities are better understood so that they are improved or newly created. The programming work is expected in C, C++, C#, assembly language, or other languages. If suitable, they can be efficiently implemented e.g. in CPU, such as x86/64, ARM, Xeon PHI, GPU, etc. or other cores in CUDA, OpenCl, VHDL, etc. Algorithms of interest include:

    • rendering using selected computer graphics methods (such as ray tracing, photon mapping, direct rendering of "point clouds", etc.),
    • processing and rendering of "lightfield" images, their acquisition, or possibly compression,
    • reconstruction of 3D scenes from images and/or video, eventually also fusing with other sensors, such as LIDAR,
    • modern algorithms of geometry suitable for applications in cpmputer graphics and perhaps also 3D printing,
    • 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.

    Collaboration on grant projects, such as TACR, H2020, ECSEL possible (employment or scholarship).

    Tutor: Zemčík Pavel, prof. Dr. Ing.

86. New approaches to optimizations

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

87. New Versions of Automata and Transducers

    .

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

88. New Versions of Automata and Transducers

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

89. Optimisation Distributed Input-Output Operations

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

90. Optimization of portofolio allocation cumulative risks

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

91. Parallel Analysis of Context-Sensitive Languages

    Tutor: Kolář Dušan, doc. Dr. Ing.

92. Parallel Analysis of Formal Languages

    Tutor: Kolář Dušan, doc. Dr. Ing.

93. Processing of Video, Image, or Signals

    The topic concerns 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.

    Collaboration on grant projects, such as TACR, H2020, ECSEL possible (employment or scholarship).

    Tutor: Zemčík Pavel, prof. Dr. Ing.

94. Processing Platform for Embedded Intelligence

    Tutor: Fučík Otto, doc. Dr. Ing.

95. Prototyping of Unmanned Aircraft System Traffic Management

    Safety, security, privacy and environmental protection are of paramount importance to respective unmanned aircraft systems (UAS) regulatory agencies. The widespread acceptance of  UAS operations depends on their ability to demonstrate compliance with domestic, regional and international regulations and policies.
    
    The present research/thesis aims to identify the technical, management and regulatory challenges facing by the UAS operation. Based on the gap analysis, the research/thesis wil try to give one big-data driven UAS Traffic Management (UTM) solution. The design of UTM will also consider the interaction and integration with the current and future Air Traffic Management(ATM) system.
    
    To make this research/thesis possible, we may introduce the resources from world-leading organizations, for example, ICAO and JARUS, and also their leaders and experts.

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

96. Quality Management Model

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

97. Reconstruction of damaged surfaces of CD/DVD/BR/HDD for forensic purposes

    The aim of the thesis is reconstruction of damaged CD/DVD/BR/HDD surfaces, consisting of:
    

    • Getting to know all possible ways of recording on CD/DVD/BR/HDD media.
    • Use of optical or electron microscope in the workplace DITS FIT BUT for scanning damaged surfaces (e.g. broken or cracked media) or in other workplaces (Tescan, Thermo Fisher - FEI).
    • Design and implementation of an application for intelligent (automatic) composition of scanned images into one unit.
    • Add intelligent functionality to read the contents of the media after the reconstruction, i.e., reconstruction or rescue of the data on the carrier.
    • Implementation of experiments and summary of achieved results.
    Participation on major international conferences and publishing in scientific or scientific journals is expected. Foreign internship is possible and strongly supported. This thesis will be dealt with in cooperation with the Police of the Czech Republic.

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

98. Safe Compilers

    Tutor: Kolář Dušan, doc. Dr. Ing.

99. Scalable neuro-evolutionary algorithms

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

100. Scalable Static Formal Analysis of Programs with Complex Data and Control Structures

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

101. Security Monitoring of Industrial Control Systems (ICS) Communication

     Industrial Control Systems (ICS) are deployed for monitoring and control of industrial processes and devices in various industrial domains: energy, machinery, transportation, etc. In the past, ICS communication was transmitted over dedicated serial lines while today's networks are transported over IPv4/IPv6 and connected with Internet.
     
     Convergence of ICS communication and IP rises security concerns and the need for security monitoring of ICS communication which includes (i) visibility of ICS transmission, and (ii) monitoring data analyses. Data analyses focuses on anomaly detection, e.g., attacks on ICS communication, malfunctioning ICS devices, etc. Unlike Internet communication, monitoring and security incident detection is still not deployed in ICS networks.
     
     The topic focuses on processing of monitoring data, enhancing ICS network visibility and application of anomaly detection methods. The research will be provided in cooperation with partners of IoT Monitoring and Forensics (IRONSTONE) research project.
     

     Tutor: Matoušek Petr, Ing., Ph.D.

102. 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.

103. Sense and Avoid Systems for Autonomous Mobility

     The advent of autonomous mobility leverages the importance of vehicle's safe collision avoidance and an elimination of the need for human monitoring. The aim of the thesis is to research an integrated opto-radio-electronic system capable of issuing alert due to nearby traffic and a real-time estimation of the collision objects' trajectories. With the increase of the Unmanned Aircraft Systems' (UAS) popularity, a reliable detection and collision avoidance becomes a necessity for autonomous UAS operation beyond visual line of sight conditions.

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

104. Scheduling and Synchronization for Multi-Core Platforms

     Multi-core solutions represent a trend in recent computational architectures and applications, primarily due to the power and thermal limitations of technology scaling. From an application perspective, it is necessary to leverage parallelism and to limit synchronization using appropriate scheduling mechanisms over available cores to meet application-specific constraints related e.g. to power consumption, quality of services they deliver, performance, dependability or timeliness of their reactions. The aim of the project is:

     • to analyze the actual state in the area of multi-core architectures and design styles of programs (user applications and their control layers based on "conventional" operating systems such as Android / Linux, Windows, iOS or specialized ones such as uC/OS-II or FreeRTOS) running over them,
     • to identify actual problems in terms of scalabilty of multi-core architectures as well as programs going to be executed by the architectures,
     • to propose a method for increasing scalability of multi-core architectures and/or programs they are designed to execute,
     • to evaluate an impact of the method to scalability.

     The project can be oriented into various directions such as multi-core system design optimization, autonomously adaptive / reconfigurable systems, task / communication scheduling or operating system architectures for multi-core systems. During the project, "conventional" multi-core platforms such as ARM Cortex-A9, Intel/AMD or specialized ones such as Xilinx Zynq 7000, Altera SoC FPGA or Microsemi Smartfusion2 can be utilized to check the proposed method in practice.

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

105. Systems based on automata and grammars

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

106. Tactical behavior modeling using machine learning and expert knowledge
     A high fidelity simulation of human tactical behavior requires the availability of human decision making process models. The subject of the thesis will be the research on scalable behavior model architectures combining machine learning approaches and domain expert knowledge to suite a range of behavior demands under various tactical scenarios. An important aspect of the design process will be the tuning and validation of the tactical decision model.

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

107. Task Based Parallelism on Heterogeneous Architectures

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

108. Testing Methods for Security Products

     Tutor: Hanáček Petr, doc. Dr. Ing.

109. Towards Inifinitely Scalable Fully-automated Highly Effective Distributed Password Recovery

     .

     Tutor: Kolář Dušan, doc. Dr. Ing.

110. Towards Inifinitely Scalable Fully-automated Highly Effective Distributed Password Recovery

     Tutor: Kolář Dušan, doc. Dr. Ing.

111. Transformation of Formal Systems for Languages

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

112. 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.

113. User and device profiling using communication patterns

     Each network communication includes specific patterns that affected by a source operating system or a source application, by frequency of sending data, behavior of an user or communicating process. Using selected attributes of the communication, e.g., packet frequency, protocol distribution, header values, or destination address distribution, we can create a communication device profile or a user profile. Device or user profiling is used in multi-level authentication systems, detection of a known device, or anomaly detection. Profiling systems can be deployed in Internet services, in IoT (Internet of Things) environment, or industrial networks.
     
     The topic focuses on development and application of technique for data extraction and processing in order to create device or user profiles. Classical methods include device fingerprinting based on device feature extraction, advanced methods use machine learning approach, e.g., clustering.
     
     The research is a part of the IGA project ICT tools, methods and technologies for smart cities and will be directed at application domains of project partners.
     

     Tutor: Matoušek Petr, Ing., Ph.D.

114. 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.

115. Using Non-Reproducibility of System Attributes in Security Area

     
     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 attributes 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 attributes.
     • 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.

116. Web Document Preprocessing for Knowledge Acquisition

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