Bioinformatics

Bioinformatics sits on the interface of computer science and molecular biology where it helps to manage, understand and analyze biological and biomedical data. Our research in bioinformatics focuses on the development of software tools applicable mainly in the domain of structural bioinformatics and visualization. These include tools for protein binding site detection, with the application in computational drug discovery, or tools for visualization of the structure of macromolecules. All our methods are implemented as software solutions used by thousands of users all over the world. Most of our tools were first implemented as bachelor or master thesis in our department.

Compilers

Compilers as the key component of high-performance computing as well as software engineering tools

Data on the web

Working with data on the Web is difficult due to numerous issues which an interested data consumer can come across, the main ones being data interoperability issues on various levels of abstraction. To support the ecosystem of data exchange on the Web, we are working on a set of techniques and tools for proper publishing and consumption of data on the Web, which include data cataloging, transformation, querying and visualization tools. We put data-centricity, data semantics and data distribution into the core of our work.

Decentralized systems

Scalable center-free systems for Internet, related to decentralized networking protocols, fault-tolerant algorithms, distributed consensus, and the related trust, security and privacy issues.

High performance computing (HPC)

Architectures, algorithms, applications in the area of high performance computing.

Multi-model databases

Relatively recently emerged NoSQL and other modern database management systems allowed to deploy databases based on other logical models than just the traditional relational. Unfortunately, the number of available models, formats, implementations, and query languages the existing systems exploit, often proprietary, is not sustainable from a longer perspective. Therefore we focus on various aspects of efficient and unified management of multi-model data, including conceptual modeling, schema inference, unified querying, or evolution management.

Multimedia Retrieval

Multimedia data penetrate all areas of our lives and become more important than ever. We meet them in social media applications, video streaming services, digital libraries as well as in specialized medical or industrial fields. As multimedia data are produced using sensors, their primary representation is semantically unstructured (e.g., an image is a bunch of pixels). Hence, recognition of what actually is inside a particular multimedia document and subsequent retrieval is a hard task that requires advanced techniques for feature extraction, object detection, similarity modeling, etc. Many of these techniques are based on machine-learning models. We carry out research in various multimedia retrieval problems and also propose many topics for student academic works (Bc, Mgr, PhD).

Recommender systems

Software that estimates, models and evaluates user preferences and needs, producing viable recommendations of items such as multimedia or goods that would match user interests.

Research Software Engineering

Optimization of scientific code to allow scientific breakthroughs.