Graduate studies

Cybernetics and Bio-inspired Systems The specialization in Cybernetics and Bio-inspired Systems integrates interdisciplinary knowledge of and competencies in, e.g., computer science, (distributed) artificial intelligence, robotics, mechatronics, electrical engineering, virtual worlds, human-computer interaction, information and communication technologies, etc. Cyber-physical systems are omnipresent, smart, and networked systems with embedded and shared sensors, processors, and actuators. They can operate in different spaces based on the principles of virtual and mixed reality and provide optimal solutions using information from both the cybernetic and real worlds. Research indicates that future applications of such systems in all spheres of human activity will lead to more significant changes than the revolution in information technologies in the past three decades. Cybernetics has laid the foundation for Industry 4.0 and is an integral part of the vision of the future Society 5.0.

Battles for better positions are already underway within emerging technologies such as MetaVerse concepts, cryptocurrencies, smart system and space concepts, and other concepts that involve security, trust, and online representation. Therefore, education in the field of cybernetics is among the key factors in the economic growth and the achieving of strategic advantages at a national level. This specialization in the field of cybernetics includes courses such as Computer Networks, Internet of Things and Cloud Computing, Mixed Reality and Design of Smart Spaces, Vision Systems, etc.

Bio-inspired systems have their foundation in the connection between phenomena observed in nature and their transposition to the technical environment with the aim of developing reliable, secure, robust, and socially acceptable technical solutions. Two fundamental branches of bio-inspired systems deal with a) the development of algorithms (evolutionary algorithms, swarm algorithms) and b) the development of technical products (bionics, humanoid robotics, soft robotics). The need for increased integration of technical products with humans and their environment assumes compatibility on multiple levels. Therefore, the study of the possibilities of applying the processes observed in nature in the development of new insights and products based on these insights is of utmost importance. In the field of bio-inspired systems, this specialization includes courses such as Evolutionary Computing, Bionics, Soft Robotic Systems, Cognitive Systems, and Functionality of Biological Systems.

Modules:

- Bionics - To familiarize students with the basics of bionic systems. Architecture of bionic systems, built in elements, possibilities and limitations of bionic systems. Application examples and future development directions.

- Computer Networks - Through lectures and exercises, students will become familiar with the basic principles of computer networks and will learn how to design and maintain networks of smaller sizes. They will also become familiar with different domains of application of computer networks, including industrial applications, the Internet and various Internet services, and the application of computer networks in realizing the vision of smart spaces.

- Evolutionary Computing - Getting familiar with the broader field of Artificial Intelligence, the narrower field of algorithms inspired by nature. Acquiring the knowledge necessary for independent design and application of evolutionary algorithms in the field of optimization and design of technical systems.

- Functionality of Biological Systems - To familiarise the students with the dynamics and hierarchical design of biological systems within the 3.5 billion years time period. Comparison of different levels of biological systems construction. The applicability of acquired knowledge about biological systems in engineering and technology design.

- Internet of Things and Cloud Computing - In this course students will learn the importance of IoT in society, the current components of typical IoT devices and trends for the future. IoT design considerations, constraints, and interfacing between the physical world and IoT device is also covered. Students will learn how to make design tradeoffs between hardware and software. The course covers the key components of networking to ensure that students understand how to connect their devices.

- Integrated production system planning - Introduction, consideration, application and research of approaches, models and procedures for integrated planning, design, optimisation and operation of production systems within the product life cycle.

- Soft robotic systems - Introducing students to the field of soft and deformable robots. Types of suitable materials, control methods, working media, sensors. Areas of application, current state and future development of the area.

- Cognitive systems - Teach students the basics of cognitive systems as a multidisciplinary branch of science that combines information science with research on human cognitive processes, while analysing information mining processes and their engineering applications in computing and technical systems.The methodology of cognitive systems is introduced through lectures and exercises, including the following: the theoretical background of cognitive informatics, which integrates data science and cognitive science, ubiquitous computing, artificial intelligence, multimodal human-environment interaction, text analysis, processing and speech, data acquisition and mining, storage and presentation of knowledge, human-system interfaces, data visualization through virtual and immersed reality, and the application of adaptability, interaction and empathy as human characteristics in the control of technical systems.

- Physical Basis of Sensors - Students will understand principles underlying functioning of diverse sensors, as well as utilise them for development of new sensors, or larger parts of measurement and testing systems.

- Mixed reality and smart spaces design - Students will learn the basics of design of virtual, extended and real spaces. They will be introduced to the concepts of physical characteristics in VR and XR environments, which can enable a positive and realistic experience of using the environment.

- Vision Systems - Gaining the knowledge required for the application of vision systems in robotics, artificial intelligence, medicine, and automatic production, including digital imaging techniques, methods of spatial and frequency domain processing of images, edge and contour detection, object recognition, 2D and 3D perception (stereovision) and their application as a part of the real environment on real systems and various software.