Creative research activitiy at faculty is orientated towards these areas:
- Automotive Innovation Lab (AIL)
- Blockchain and FinTech (BlockFin)
- Artificial Intelligence and Knowledge Discovery (brAInworks)
- Cyber Security and IoT (CSI)
- Computer Vision and Computer Graphics (VGG)
- Intelligent Data and Systems with Applications (IDSA)
- ETHOS-AI Research Group (Efficient TrustwortHy and rObuSt Artificial Intelligence)
- Human-Robot Interactions Lab (HRILab)
Research group focused on the development of intelligent sensors and communication architectures in the V2X environment and smart transport primarily for the purpose of research in the field of safety systems and related interconnectivity.
In ongoing projects, we focus specifically on the area of connected vehicles and related communication architectures, monitoring the fluidity and especially road safety in line with the European Commission 's vision for Vision Zero - to achieve almost zero fatalities on European roads by 2050.
Keywords:
Heterogeneous network management, V2X applications, V2X networking, Smart ADAS, Wireless Networks, 5G, LEO Satellite Internet
A diverse group of researchers at FIIT are working on a range of Blockchain academic and industry-driven research projects in a means to push further the technical development and innovation of the endless applications of Blockchain.
Current research projects of BlockFin include: connection to IoT platforms and it's usability, distributed systems, data mining and machine learning, anti-money laundering techniques, scalability and resiliency, smart contracts, non-fungible tokens (NFTs), blockchains interoperability, voting and election systems based on blockchain, privacy and security in blockchains and cryptocurrencies, asset sharing blockchain platforms, metaverse projects, decentralized finances (DeFi), and others.
The vision of the group lays in approaching Internet of Value in a horizon of 5 to 10 years and further empowering blockchain technology usage in society, actually, especially metaverse.
Keywords:
Blokchain, Blockchains Interoperability, Distributed Lefger Technology, Interoperability, Asset Sharing Blockchain Platforms, Nft, Anti-Money Laundering, Payment Gateways
The methodologies that clinicians use to decide on a patient's treatment are ever changing. It seems to us that 21st century cancer medicine is much about analysing big data and using AI and statistical learning to extract information that can predict how diseases will evolve and react to therapies. However, the sad fact is that despite ever increasing effort in the field there is no tangible progress in transferring that knowledge into “bedside” practice. To this end, the brAInworks project aims to fill this gap by developing novel AI-driven real-time strategies for knowledge discovery and monitoring human disease progression such as cancer.
Keywords:
AI, Statistical Learning, Cancer Genomics, In Silico Medicine, Hierarchical Non-Parametric Bayesian Modelling, Longitudinal Modelling, Spatial Modelling, Imaging, Risk Estimation, Early Disease Detection
Modern world is dependent interconnected systems, devices, sensors and their reliable operation. CSI research group tackles research challenges in areas of data security and privacy, cryptography, network and system security. CSI also pays special attention to the research of designing energy efficient and secure IoT devices and communication.
Keywords:
Computer Security, Risk Analysis, Security Standards, Security Model, Security Mechanisms, ISO/IEC 27000, Public Key Infrastructure, Access Control, Mobile Networks, Routing
Research in applications of computer vision and AI methods in the domains of medical imaging and digital pathology for automatic processing of radiological and microscopic images for the purpose of qualitative and quantitative analysis. Computer vision using Deep Neural Networks in medical domain applications and modeling of human visual attention is the main research focus of the group.
Keywords:
Medical Imaging, Object Detection and Object Recognition in 2D / 3D, Visual Attention Prediction, Augmented and Virtual Reality Applications, Big Data Visualization
The IDSA research group at FIIT STU focuses on innovative data intelligence and computational intelligence solutions towards building AI-assisted systems and applications using data-driven technologies with respect to information privacy and security. We are exploring various aspects of intelligent data and computing, as well as AI in IT operations (AIOps) toward responsible AI and business impacts with a strong focus on education.
Keywords:
Responsible AI • AIOps • Natural Language Processing •
NeuroEvolution • Green Computing • Information Privacy and Security
The ETHOS-AI research group focuses on developing efficient, trustworthy, and robust Artificial Intelligence (AI) methods for high-impact applications, with a particular emphasis on healthcare and biomedical systems. The group addresses key challenges in modern AI, including reliability, interpretability, uncertainty representation, human-centred design, and safe integration of AI technologies into clinical practice.
Keywords:
Trustworthy Artificial Intelligence, Uncertainty Quantification, Explainable AI, Robust Machine Learning, Medical Artificial Intelligence, Human–AI Interaction, UX Design for Healthcare, Clinical Decision Support, Medical Image Analysis, Personalised Healthcare AI
HRILab is a multidisciplinary research group focused on investigating and developing technologies that intelligently and naturally connect people with digital and physical environments. Our research covers Human-Computer and Human-Robot Interaction (HCI/HRI), User Experience, adaptive and intelligent learning systems, eHealth informatics and social robotics, as well as VR/AR/XR technologies and intelligent software engineering. We investigate user modeling, adaptive interfaces, human-centered AI, neuroadaptive interaction, intelligent data analysis, and generative AI to create personalized, context-aware, and human-centered digital systems. An important part of our research is the connection of these areas with Educational Content Engineering, where we apply and adapt proven software engineering best practices—including modeling, reuse, evolution, testing, quality evaluation, and collaborative curation—to the engineering of shareable, adaptive, and high-quality educational content.
Keywords:
Human-Computer Interaction (HCI); Human-Robot Interaction (HRI); User Experience (UX); Adaptive Learning; Educational Content Engineering; Learning Objects; Collective Intelligence; Human-Centered AI; Social Robotics; eHealth Informatics; Telemedicine; Neuroadaptive Interaction; VR/AR/XR; Intelligent Software Engineering; Generative AI; User Modeling; Adaptive Interfaces; Human-Technology Interaction; Modeling; Reusability; Software Engineering Best Practices
The IDSA research group at FIIT STU focuses on innovative data
intelligence and computational intelligence solutions towards building
AI-assisted systems and applications using data-driven technologies with
respect to information privacy and security. We are exploring various
aspects of intelligent data and computing, as well as AI in IT
operations (AIOps) toward responsible AI and business impacts with a
strong focus on education.