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.

• Graduates from the doctoral study programme are trained to independently work in research, development, or management.
  
• They are able to solve and/or to lead teams solving advanced conceptual, research, development, or production problems in the area of contemporary information technology and its applications.
  
• They can be engaged to work on creative tasks, to lead research and development teams, or to work in management of companies or organizations whenever there are required abilities to work in an independent and creative way, to analyze complex problems, and to propose and realize new and original solutions. Graduates from the doctoral study programme can also teach and/or scientifically work at universities.

prof. RNDr. Milan Češka, CSc.

1. Acceleration of ultrasound simulations in bones

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

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, and so that they are 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 programming work is expected in C, C++, C#, assembly language, CUDA, OpenCl, VHDL, or other. 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., dr. h. c.

3. Advanced approaches in cellular automata design

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

4. Advanced bioinformatic tool for computer design of proteins

   Tutor: Zendulka Jaroslav, doc. Ing., CSc.

5. Advanced Computing System for Numerical Solution of Differential Equations

   Tutor: Kunovský Jiří, doc. Ing., CSc.

6. Advanced methods for security analyses of event logs

   Tutor: Matoušek Petr, doc. Ing., Ph.D., M.A.

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

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

8. Algorithms of Advanced Image and Video Processing

   The topic focuses algorithms of image and video processing. 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, and so that they are 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. The programming work is expected in C, C++, C#, assembly language, CUDA, OpenCl, or VHDL. The algorithms of interest include:

   • recognition of scene contents, events, and general semantics of video sequences,
   • classification of video sequences through deep convolution networks neural networks, space-time features, etc.,
   • object tracking in video using modern methods (such as TLD or particle tracking)
   • assessment of video content similarities and its contents e.g. through mutual information, semantics analysis,
   • new algorithms of video Processing 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., dr. h. c.

9. Analysis of Anonymisation Networks Security

   Tutor: Hanáček Petr, doc. Dr. Ing.

10. Analysis of Attacks on Wireless Networks

    Tutor: Hanáček Petr, doc. Dr. Ing.

11. Analysis of Presence and Motion of Pedestrians in Video
    • Research and development of computer vision algorithms.
    • Focus on videos from interior/exterior surveillance cameras.
    • Research of algorithms avoiding user input.
    • Implementation of experimental prototypes.
    • Design and development of application demonstrators.

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

12. Approximate computing in low-power video processing

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

13. 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.

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

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

15. Automatic Transformation of Ordinary Differential Equations

    Tutor: Kunovský Jiří, doc. Ing., CSc.

16. Automatic Workload Balancing on Heterogeneous Architectures

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

17. Automatized Definition of Context-Sensitive Grammars

    Tutor: Kolář Dušan, doc. Dr. Ing.

18. Autonomous Inelligent Systems Driven by a Models

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

19. Bayseian networks - constructions and applications

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

20. Big Data and Analysis of Business Processes for Industry 4.0

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

21. Big Data and Analysis of Business Processes for Industry 4.0

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

22. Big Data and Analysis of Business Processes for Industry 4.0

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

23. Big Data and Analysis of Business Processes for Industry 4.0

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

24. Big Data and Analysis of Business Processes for Industry 4.0

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

25. Communication Infrastructure for Intelligent Buildings or Vehicles

    Tutor: Hanáček Petr, doc. Dr. Ing.

26. Communication Monitoring Based on Device Profiles

    Tutor: Matoušek Petr, doc. Ing., Ph.D., M.A.

27. Deep Pushdown Automata: Theory and Applications

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

28. 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.

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

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

30. 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.

31. 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.

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. Digital Circuits Based on Ambipolar Devices

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

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

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

35. Distributed Photoacoustic Imaging

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

36. Efficient Techniques for Dealing with Automata and Logics and Their Applications

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

37. Efficient Techniques for Dealing with Automata and Logics and Their Applications

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

38. Efficient Techniques for Dealing with Automata and Logics and Their Applications

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

39. Evolutionary synthesis of complex digital circuits

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

40. Formal Grammar and Automata Systems

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

41. Formal Models of Distributed Computation

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

42. General Purpose GPU

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

43. Hybrid Reprogrammable Processing Platforms

    Tutor: Fučík Otto, doc. Dr. Ing.

44. Image recognition and machine learning in service robotics

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

45. Information Extraction from Wikipedia and Other Web Sources

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

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

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

47. Interaction of speech recognition and data mining

    Speech recognition systems are nowadays rarely used alone, but are parts of more complex data processing chains, both in military-security and business scenarios. Typically, they are integrated with a machine translation system and the following data-mining, for example topic detection, sentiment/emotion analysis or business data extraction. As many of these systems are nowadays based on DNNs or their variants, there is a possibility of joint training of such system optimizing the final goal of the system.
    
    The proposal is related to ongoing EU H2020 project Bison, and US DARPA funded Lorelei project.
    

    Tutor: Černocký Jan, prof. Dr. Ing.

48. Intrusion Detection and Automatic Processing of Malware

    Tutor: Hanáček Petr, doc. Dr. Ing.

49. IoT Processor Design

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

50. Low-power deep learning on a chip

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

51. Methods for Pattern Extraction and Detection in Program Code

    Tutor: Kolář Dušan, doc. Dr. Ing.

52. Modeling and Analysis of Fault-Tolerant Systems

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

53. Modern and Accelerated Visal Computing Algorithms

    Tutor: Zemčík Pavel, prof. Dr. Ing., dr. h. c.

54. Multispectral analysis of human tissues for medical purposes

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

55. Neural Networks for Deep Learning

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

56. New approaches in Neural Network Theory

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

57. New Trends in Numerical Solutions of Differential Equations

    Tutor: Kunovský Jiří, doc. Ing., CSc.

58. New Versions of Automata and Grammars

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

59. Optimisation Distributed Input-Output Operations

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

60. Parallel Analysis of Context-Sensitive Languages

    Tutor: Kolář Dušan, doc. Dr. Ing.

61. Parallel Analysis of Formal Languages

    Tutor: Kolář Dušan, doc. Dr. Ing.

62. Prototyping of sensor systems by multiagent systems

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

63. Quality-driven approximate computing systems

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

64. Real Robots Planning Algorithms

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

65. 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.

66. Rouhg Sets and Big Data

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

67. Safe Compilers

    Tutor: Kolář Dušan, doc. Dr. Ing.

68. Security monitoring of IoT Communication

    Tutor: Matoušek Petr, doc. Ing., Ph.D., M.A.

69. Semantic web portal generator

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

70. Specialized Parallel Processor Computation Organization

    Tutor: Kunovský Jiří, doc. Ing., CSc.

71. Spoken message aware speaker recognition

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

72. Static Analysis and Bug Finding in Software

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

73. Synthesis of Stochastic Models

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

74. System for the detection and recovery of transient faults in FPGA based systems

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

75. Testing Methods for Security Products

    Tutor: Hanáček Petr, doc. Dr. Ing.

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

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

77. Traffic estimation nad prediction

    Tutor: Fučík Otto, doc. Dr. Ing.

78. Traffic simulation

    Tutor: Fučík Otto, doc. Dr. Ing.

79. Transformation of Models for Formal Languages

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

80. 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.

81. User interfaces based on non-contact technologies

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

82. Video content and video collection summarization

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

83. Visual Geo-Localization on Mobile Devices

    The project deals with geo-localization of mobile devices in unknown environments using computer vision and computer graphics methods. The aim is to investigate and develop new image registration techniques (with geo-localized image database or 3D terrain model). The goal is an efficient implementation of proposed methods on mobile devices as well as search for additional applications in the area of image processing, computational photography, and augmented reality.
    

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

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

84. Visual Geo-Localization on Mobile Devices

    The project deals with geo-localization of mobile devices in unknown environments using computer vision and computer graphics methods. The aim is to investigate and develop new image registration techniques (with geo-localized image database or 3D terrain model). The goal is an efficient implementation of proposed methods on mobile devices as well as search for additional applications in the area of image processing, computational photography, and augmented reality.
    

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

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

85. Visual Geo-Localization on Mobile Devices

    The project deals with geo-localization of mobile devices in unknown environments using computer vision and computer graphics methods. The aim is to investigate and develop new image registration techniques (with geo-localized image database or 3D terrain model). The goal is an efficient implementation of proposed methods on mobile devices as well as search for additional applications in the area of image processing, computational photography, and augmented reality.
    

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

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

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

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

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

89. Tutor: Kolář Dušan, doc. Dr. Ing.

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

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

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