Research groups

Centre for Artificial Intelligence in Oncology joins experts from various fields and organizations in the research of the origin, diagnosis and treatment of cancer.

Our main focus is on biomedical image analysis using deep learning, but we also attend to data mining of patient records. We foster dialogue and collaboration of experts of different backgrounds coming from universities, research institutes, hospitals, and industry. We interconnect computer science, biology, and medicine in the studies of cancer genesis, diagnostics, and treatment.

The DYSLEX research team integrates machine learning analytics with eye-tracking technology to refine diagnostic approaches for dyslexia. This interdisciplinary team, composed of experts in fields such as education, psychology, AI, eye-tracking, machine learning, and educational-psychological practice, analyzes dyslexic students' eye movements to enhance the precision of diagnostics. The aim is to advance the diagnostic processes and intervention strategies for this widespread, specific learning disorder. Key goal is to improve intervention strategies for dyslexic students, aiming for more tailored and effective educational support.

Adaptive learning environments are computer applications that adapt to the knowledge of a particular student. The research group deals both with the practical development of such systems and with the related theoretical research. The group intensively collaborates with the spin-off Umíme, which is a key online learning platform in Czech Republic.

Artificial intelligence is used in two ways. First, for algorithms that guide the behavior of a learning environment (e.g., question construction of recommendation of learning activities). Second, for augmenting intelligence of human designers by providing analysis of massive data collected by learning environments.

The Laboratory of Formal Methods, Logic, and Algorithms (Formela) concentrates on applications of logic, game theory, and discrete structures in computer science. Special attention is devoted to algorithms and methods for formal analysis and verification of computer systems, applications of game theory in artificial intelligence, and also to emerging topics at the frontiers of formal methods and AI.

The Knowledge Discovery Lab focuses its research on anomaly analysis, automated machine learning, and neuro-symbolic learning, aiming to enhance the performance of deep networks. Special emphasis is placed on collaboration with other faculties of Masaryk University and foreign workplaces and universities. The laboratory also contributes to the teaching of advanced machine learning courses at FI MU.

LiVe Lab concentrates on the interactions between AI/ML and verification, both in the direction of using AI to improve verification as well as verifying systems with AI-based components. Special attention is devoted to verification and monitoring of neural networks, safety and guarantees in reinforcement learning, explainability of cyber-physical controllers and artefacts of verification, or AI-aided techniques for verification of probabilistic systems and games.

The Natural Language Processing Centre (NLP Centre) at the Faculty of Informatics, Masaryk University, conducts theoretical and applied research in the following areas: analysis of written texts at all levels - morphological, syntactic, and semantic; corpus management and lexical databases; semantic representation of natural language expressions; semantic web, ontologies, knowledge representation and reasoning; applications of machine learning techniques to text processing; dialog representation and management; synthesis and recognition of speech.

In terms of downstream applications, the research focuses on human-machine communication and Internet technologies focused on text and speech analysis, mining and generation.

In addition to its research objectives, the NLP Centre concentrates on the participation of undergraduate and postgraduate students in the interdisciplinary specialization of "language engineering".

RationAI research group, founded by researchers from the Faculty of Informatics and Institute of Computer Science at Masaryk University, concentrates on developing cutting-edge AI methods in biomedicine. We aim to create an appropriate environment that will maximally support cooperation between domain experts and computer science specialists, focusing on explaining the behavior of these AI methods (explainable AI, XAI). As an indispensable part of such an effort, we consider traceable development, training, and validation of the AI methods using automated provenance information generation and robust visualization systems. Furthermore, for specific domains, we also develop a trusted environment for the validation of AI methods using evaluation metrics developed in tight cooperation with the domain experts.

We have active collaboration with groups from Masaryk Memorial Cancer Institute (pathology), MagicWare company (obesitology), Biobanking and BioMolecular resources Research Infrastructure – European Research Infrastructure Consortium (large biomedical datasets), Medical University Graz (pathology, data security).

We welcome students of all levels to participate in exciting interdisciplinary research in artificial intelligence.

The Institute deals with legal and ethical issues in AI. Legal protection of data used in machine learning - personal data protection, privacy, personality protection, intellectual property, non-personal data protection; machine processing of public sector information; rights related to the output of generative systems; regulatory compliance of AI systems - compliant development and deployment of AI, certification, auditing; AI liability; autonomous decision-making; judicial and legal applications of AI - autonomous generation of evidence, processing of legal language, generative technologies in legal applications.

The Loschmidt Laboratories are based at Masaryk University (RECETOX and the Institute of Experimental Biology) and at the International Clinical Research Center of the St. Anne's University Hospital in Brno. The laboratory conducts interdisciplinary research in the field of protein engineering.

Proteins are the natural building blocks of all living organisms and participate in virtually all cellular processes. Through its research, the laboratory aims to understand the relationships between protein structure and function, improve their functionality for biotechnology, study the mechanisms of Alzheimer's disease, and develop new drugs for acute stroke.

Dr. Stanislav Mazurenko's artificial intelligence team is part of the Loschmidt Laboratories and applies machine learning methods to various types of data. They develop state-of-the-art approaches to decipher patterns in experimental measurements, protein sequences, and dynamic structures. The team's goal is to gain insight into fundamental biophysical mechanisms, create reliable and interpretable software tools for designing improved protein variants (see https://loschmidt.chemi.muni.cz/portal/), and provide support for decision-making, experiment design, data analysis, and drawing conclusions. The team is an active member of the ELIXIR ML Focus Group.

In the field of machine learning, the team actively collaborates with the Czech Institute of Informatics, Robotics, and Cybernetics in Prague, It4Innovation in Ostrava, the Technical University of Copenhagen, and the University of Texas at Austin.

The DeePsy team is involved in the development of a web application (DeePsy.cz) designed to assist psychotherapists in routine care. The DeePsy app serves to routinely monitor the processes and outcomes of psychotherapy and provides constant feedback to psychotherapy practitioners with the goal of enhancing the quality of psychotherapy. The team consists of experts in the fields of psychology, psychotherapy, and speech processing who work together to integrate the clinical knowledge and experience with the ever-increasing possibilities of automated data processing.