Computer Science

Interactive multimedia 

Interactive media are generally digital media, while multimedia elements include computer graphic design (including 2D and 3D animation), digital photography, video, sound, and text carrying information. Techniques used in multimedia interaction include not only signal processing, but also machine learning methods, including deep neural networks.

Career prospects:

A graduate of the "Interactive Multimedia" track, as a specialist in various types of multimedia interfaces, can find employment in many professions related to computer systems. They can work as an interaction designer, user experience and usability evaluation specialist, audio/video developer, text mining/data mining specialist, machine learning and pattern recognition specialist, computer vision and natural language specialist, speech synthesis/recognition specialist, usability and design specialist, multimedia application programmer, and many others.

The subjects most specific to this profile in the curriculum are:

— Digital signal and image processing;
— Advanced multimedia techniques
— Linguistic engineering;

Candidate profile:
Candidates should have basic knowledge and skills in the area of programming and multimedia handling.

Graduate competencies:

• Knows and applies the principles and techniques of user interface design and testing;
• Possesses comprehensive knowledge in the area of multimodal, voice, and graphical user interfaces (GUIs), mobile device interfaces, motion-based interfaces (e.g., Kinect), and others;
• Understands the principles of system and interface accessibility, as well as creating interfaces dedicated to special user groups, e.g., people with disabilities;
• Possesses knowledge in the area of computational linguistics;
• Knows the principles of text data analysis and information extraction from texts;
• Is able to use natural language processing (NLP) technologies, automatic speech recognition and translation, as well as speech synthesis; 
• Uses tools for creating ASR (automatic speech recognition) and SMT (statistical machine translation) systems;
• Knows and can apply digital signal and image processing techniques, sound and image processing techniques, and graphics generation;
• Knows classification and object recognition methods;
• Applies virtual and augmented reality techniques;

Examples of completed thesis topics:

• A speech synthesis system based on an acoustic database recorded by a non-professional speaker.
• An image segmentation method for sidewalk recognition using convolutional neural networks.
• Voice quality classification using the RBH scale and deep neural networks.
• The impact of used graphical user interfaces in video games on the perception of gameplay mechanics by different types of players.
• Aphastory – an application designed for people affected by aphasia using Google Glass.
• A mobile application to support the rehabilitation process of people affected by sensory aphasia.
• Aphasia Planner – a mobile application project for people affected by aphasia.
• Hybrid music recommendation system.
• Improving manual testing processes through the implementation of automated tests.

List of supervisors:

- dr hab. Sc. Krzysztof Szklanny, Prof. PJAIT
- dr hab. .Sc. Ryszard Gubrynowicz, Prof. PJAIT
- dr hab. .Sc. Alicja Wieczorkowska, Prof. PJAIT
- D.Sc. Mariusz Kleć
- D.Sc. Piotr Wrzeciono
- M.Sc. Michał Żbikowski
- M.Sc. Maksymilian Kubica
- M.Sc. Hai Duong Minh