Creative research activitiy at faculty is orientated towards these areas:
- Advanced Software Development Research Group (AdvanSD)
- 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)
The AdvanSD research group explores various aspects of software development. Currently, our focus is on representing and reusing software knowledge and software comprehension and quality.
Interrelating and Visualizing Heterogeneous Software Knowledge, Multidimensional Software Modeling, Agile and Lean People, Organization, Software Processes, Social Connotations, Software Product Lines and Variability, Software Patterns, Intent Comprehensibility, Use Case Driven Modularization, Advanced/Aspect-Oriented Modularization, Software Quality, Refactoring, Automated Testing and Continuous Revisions, Software Modeling Beyond Software Development, Education for Software Development and Supported by Software Development, Visualization of Software Properties
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.
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 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 applications of blockchain into normal life.
Blokchain, Blockchains Interoperability, Asset Sharing Blockchain Platforms
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.
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. Our research group tackles research challenges in areas of data security and privacy, cryptography, network and system security and system security. We also pay special attention to the research of designing energy efficient and secure IoT devices and communication.
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 artificial intelligence 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.
Medical Imaging, Object Detection and Object Recognition in 2D/3D, Visual Attention Prediction, Augmented and Virtual Reality Applications, Big Data Visualization