Project
Institute of Informatics
International Projects
ViWAS - Virtual Worlds Skills Academy (ViWAS)
Akadémia zručností virtuálnych svetov
| Duration: | 1. 5. 2026 - 30. 4. 2030 |
| Evidence number: | 101298981 |
| Program: | Horizont Európa |
| Project leader: | Ing. Tran Viet PhD. |
| Annotation: | The rapid evolution of immersive digital technologies such as virtual reality (VR), augmented reality (AR), and extended reality (XR) has led to the emergence of Virtual Worlds (VWs) as transformative tools across sectors. However, the education and training landscape has yet to fully respond to the growing demand for specialized VW-related skills. The Virtual Worlds Skills Academy (ViWAS) aims to bridge this skills gap by developing a comprehensive, future-proof competence and training ecosystem that equips learners, educators, and professionals with the necessary capabilities to thrive in and shape the VWs economy. ViWAS is a pioneering educational initiative that combines the power of RenDanHeYi (2021) organisational model with the agility of the franchise system in an educational context. ViWAS has a cloud-enterprise-like modern structure and aims to prepare the future developers, teachers, architects, designers, and users of VWs through a fundamentally new approach to education that relies on AGILE structures, design thinking, and an entrepreneurial mindset. It will contribute to the EU’s digital transformation by upskilling and reskilling the workforce in the fast-growing field of VW. By fostering collaboration between education providers, industry, and policymakers, ViWAS will pave the way for inclusive, innovative, and sustainable digital learning environments across Europe. ViWAS is focusing on teaching and learning skills for, about and with VWs, developing a network of learning centres that can rapidly adapt to the dynamic evolution of VW, placing the learner at the centre of the educational process and fostering an entrepreneurial spirit and design thinking approach at every level |
ENSURE - ENvironmentally SUstainable digital services and practices for REsearch infrastructures (ENSURE)
Environmentálne udržateľné digitálne služby a postupy pre výskumné infraštruktúry
| Duration: | 1. 9. 2026 - 31. 8. 2029 |
| Evidence number: | 101292847 |
| Program: | Horizont Európa |
| Project leader: | doc. Ing. Hluchý Ladislav CSc. |
| Annotation: | The digital transformation of science depends on large-scale Research Infrastructures (RIs) that generate, process, and store unprecedented volumes of data. However, their environmental footprint is rapidly increasing, raising concerns about energy and water use, carbon emissions, and sustainability. ENSURE addresses this challenge by operationalising the 4M cycle (Measure, Model, Monitor, Moderate) to reduce the environmental footprint of digital RIs while safeguarding scientific excellence. ENSURE will develop new technologies that combine environmental metrics, reference datasets, benchmarks, and advanced monitoring tools into a coherent framework. Harmonised indicators, aligned with international standards and EU legislation, will provide a trusted basis for impact assessment and reporting. Digital twins of data centres and GenAI methods will enable predictive modelling and the filling of data gaps related to digital infrastructure operations. Workload managers will integrate sustainability into scheduling and resource allocation, while certification and reporting frameworks will ensure transparency, comparability, and accountability across RIs. The consortium unites major ESFRI Landmarks (HL-LHC, SKA, European XFEL), pan-European digital infrastructure providers (EGI), life science domain communities (WeNMR, VIP), leading research universities, and sustainability experts. This unique composition ensures scientific relevance, technical excellence, and broad uptake across disciplines from physics, astronomy, life sciences, and medical imaging to the whole RI landscape. By embedding environmental sustainability into the daily operation of digital RIs, ENSURE will contribute directly to the European Green Deal and climate neutrality objectives. The project’s outcomes will not only lower the environmental footprint of research infrastructures but also position Europe as a global leader in sustainable digital science. |
EOSC Beyond - EOSC Beyond: advancing innovation and collaboration for research
EOSC Beyond: pokrok v inováciách a spolupráci v oblasti výskumu
| Duration: | 1. 4. 2024 - 31. 3. 2027 |
| Evidence number: | 101131875 |
| Program: | Horizont Európa |
| Project leader: | Ing. Tran Viet PhD. |
| Annotation: | EOSC Beyond overall objective is to advance Open Science and innovation in research in the context of the European Open Science Cloud (EOSC) by providing new EOSC Core capabilities allowing scientific applications to find, compose and access multiple Open Science resources and offer them as integrated capabilities to researchers. To do so, EOSC Beyond supports a new concept of EOSC: a federated and integrated network of Nodes operated at different levels, national, regional, international and thematic, to serve the specific scientific missions of their stakeholders. Further specific objectives of the project are to accelerate ‘time to product’ of new scientific applications with software adapters, enable Open Science with machine composability and dynamic deployment of shared resources, support innovation in EOSC with a testing and integration environment, and align the EOSC Core architecture and specifications to integrate with European dataspaces. The project extends the state of the art of the EOSC Core and adopts a co-design methodology, including requirements elicitation, software development and validation in collaboration with different use cases from EOSC national and regional initiatives (e-Infra CZ, Czechia, NFDI, Germany, and NI4OS, South East Europe region), thematic research infrastructures from Social Sciences and Humanities (CESSDA), Life Sciences (CNB-CSIC and Instruct-ERIC), Environmental Science (ENES and LifeWatch), and Health and Food (METROFood-RI). EOSC Beyond builds on the capacities of prospective EOSC Nodes and partners with multi-annual experience in developing solutions for large-scale federated digital infrastructures and aligns with the technical architecture and requirements of data spaces from different business sectors. Ultimately, EOSC Beyond supports Open Science in modern, data-intensive, and multidisciplinary research, facilitating resource discovery, access, and reuse across scientific communities, organisations, and countries. |
| Project web page: | https://www.eosc-beyond.eu/about |
NERO - European network on extreme fire behavior (NERO)
Európska sieť pre extrémne správanie požiarov
| Duration: | 17. 10. 2023 - 16. 10. 2027 |
| Evidence number: | CA22164 |
| Program: | COST |
| Project leader: | RNDr. Glasa Ján CSc. |
| Project web page: | https://www.cost.eu/actions/CA22164/#tabs+Name:Description |
FLUID-AI - FAIR Liquidity Unifying Interoperable Data and AI (FLUID-AI)
FAIR likvidita zjednocujúca interoperabilné dáta a umelú inteligenciu
| Duration: | 1. 10. 2026 - 30. 9. 2029 |
| Evidence number: | 101292610 |
| Program: | Horizont Európa |
| Project leader: | Ing. Tran Viet PhD. |
| Annotation: | The FLUID-AI project introduces a new approach to address the lack of interoperability between data, AI/ML models and solutions within the EOSC. We introduce the concept of Data and Models Liquidity, building on and extending the FAIR principles to address the unique demands of AI-ready data and models. While the FAIR principles have improved data management, they fall short in supporting AI applications, which require data that are not only FAIR but also structured, annotated, and optimized for seamless integration into AI/ML workflows. FLUID-AI identifies and addresses 3 major gaps within the EOSC ecosystem. First, we establish a collaborative Competence Centre (CC) to provide coordinated support, training, and resources, ensuring researchers and operators are equipped with the skills needed to leverage AI/ML tools effectively. Secondly, we promote unified data and models integration, implementing semantical and technical interoperability to enable effortless reuse and combination across platforms and scientific disciplines. Thirdly, we deliver accessible and intuitive platforms, reducing technical complexity so researchers can focus on scientific discover. The project is organized in 3 different action pillars corresponding to the identified gaps. Together with 8 real-world use cases from representative Research Infrastructures would allow us to demonstrate the FLUID-AI impact, validating the project’s solutions, ensuring they are scalable, reproducible, and aligned with real-world research needs. By promoting cross-disciplinary collaboration, standardization, and open science principles, FLUID-AI aims to transform the EOSC into a dynamic, AI-ready ecosystem. The project outcomes include the novel Data and Models Liquidity concept and framework, innovative tools and platforms, comprehensive guidelines, and a blueprint for trustworthy AI-ready repositories. All together will empower researchers to leverage the full potential of AI-driven scientific discovery. |
GenAI4Earth - Generative Artificial Intelligence for Earth System (GenAI4Earth)
Generatívna umelá inteligencia pre systém Zeme
| Duration: | 1. 9. 2026 - 31. 8. 2029 |
| Evidence number: | 101293266 |
| Program: | Horizont Európa |
| Project leader: | Ing. Tran Viet PhD. |
| Annotation: | Generative Artificial Intelligence (GenAI) is rapidly advancing, offering novel ways to exploit multi-disciplinary data and generate new knowledge for science. In Earth System Science (ESS), GenAI is emerging as a transformative technology, enabling a paradigm shift in understanding, predicting, and managing complex socio-environmental systems by cross-using diverse yet fragmented data sources (satellite and in-situ observations, models, experiments, texts). GenAI4Earth will go beyond the state of the art by designing, deploying, and operating trustworthy, reusable GenAI services within the EOSC ecosystem, advancing discovery on Earth–climate–environment– life interactions in co-design with user communities and research infrastructures at national and European levels. Aligned with GenAI4EU and Apply AI initiatives, the project builds on FAIR data, models, and workflows, integrating them into EOSC (AI4EOSC, EOSC Nodes such as Data Terra and NFDI) to foster standards, best practices, and confidence in AI-enabled dataspaces and foundation models. Concretely, GenAI4Earth will: • Develop GenAI tools to enhance FAIRness, machine-actionability, AI-readiness, and provenance of ESS data and services; • Implement AI-powered interfaces for seamless discovery, access, and cross-domain integration; • Demonstrate pilots in urban resilience, agro-environmental monitoring, and seismology through topical AI foundation models; • Promote responsible AI with reproducibility, explainability, transparency, and frugal computing; • Build capacity via training and engagement to ensure broad uptake of GenAI-enabled workflows. The consortium mobilises expertise across AI, data science, Earth systems, computing infrastructures, and ethics to co-design interoperable, reproducible, and impactful services. |
Chemiresistive sensors based on 2D nanomaterials
Chemorezistorové senzory na báze 2D nanomateriálov
| Duration: | 1. 1. 2025 - 31. 12. 2026 |
| Evidence number: | Mobilita SAS-BAS-2025-2026 |
| Program: | Mobility |
| Project leader: | Ing. Predanocy Martin PhD. |
| Annotation: | This project proposal builds on the previous project BAS-SAS-2022-05, which focused on investigating new progressive nanostructured 2D materials based on dichalcogenides of transition metals. In this project, we propose to focus on graphene as a 2D material for developing chemiresistive sensors. The subject of this project proposal is research concerning the preparation methods of nanometer patterns in 2D graphene using electron beam lithography, one of the alternative methods for creating nanometer patterns. An important part of the project is addressing the problems associated with the interaction of the electron beam in a very thin electron beam resist (10 - 50 nm) on 2D materials, including graphene. We will conduct experimental examinations and simulations of lithographic parameters on very thin electron beam resists on 2D graphene. We expect to observe new scattering effects that need to be analyzed and clarified in the case of low-energy secondary electrons. Additionally, the scattering of backscattered electrons, which involves long-range electron scattering in the substrate, will be examined. |
CPS4EM - Cyber-Physical System for environmental monitoring and data analysis
Kyberneticko-fyzický systém pre monitorovanie životného prostredia a analýza údajov.
| Duration: | 1. 1. 2025 - 31. 12. 2026 |
| Evidence number: | BAS-SAS-2024-01 |
| Program: | Mobility |
| Project leader: | Ing. Zelenka Ján PhD. |
| Annotation: | The aim of the project is research and development of Cyber-Physical System (CPS) for environment monitoring, including the following embedded systems: hardware, software, sensors, IoT devices, communication system, data evaluation techniques and web-based user interface containing the necessary functions for work in an outdoor environment. This main complex system will be controlled via the Internet but alternative communication links will also be considered. Thus the system can be used as a warning system in domain precision agriculture of forestry management or environmental monitoring devices monitoring natural disasters. The project will boost up the cooperation of two academic institutions with complementary research activities. Participating PhD students and young researchers will gain experience from international cooperation, from which they will benefit in their further professional career. |
EOSC-ARENA - AI Research Enhancement through Networked Agents (EOSC-ARENA)
Vylepšnie výskumu umelej inteligencie sieťovými agentami
| Duration: | 1. 6. 2026 - 31. 5. 2029 |
| Evidence number: | 101292597 |
| Program: | Horizont Európa |
| Project leader: | Ing. Tran Viet PhD. |
| Annotation: | The EOSC-ARENA (AI Research Enhancement through Networked Agents) will deliver a sovereign, generative and agentic Artificial Intelligence (AI) environment integrated with the European Open Science Cloud (EOSC). This AI environment will serve as a scientific assistant supporting the full research lifecycle, from literature review and hypothesis generation to analysis, reporting, and provenance capture. The project responds to pressing needs in the use of smart algorithms and AI/ML services in scientific research, fostering trust, transparency, and European technological sovereignty. The project focuses on building an advanced, scalable, multi-agent system and a marketplace for Generative AI (GenAI) agents and services. It will provide federated training and inference, secure generation with augmented search and integrations based on the Model Context Protocol. The EOSC-ARENA system will be deployed on EU e- infrastructures and interoperable with EOSC EU nodes. Twelve real-life use cases from different scientific domains are selected to co- design, implement, and assess the effectiveness of the project solutions. At the same time, we will provide community engagement, skills development and guidance for responsible, human-centric AI that aligns with EU values and the Research Integrity Framework. Main outcomes include an EOSC-ready platform release with agent execution and marketplace, open-source components, machine-actionable APIs and provenance mechanisms. Equally important will be policy guidance and training assets to accelerate trustworthy AI adoption. The project targets demonstrators integrated with EOSC services and contributes directly to the EOSC and its strategic research and innovation agenda by strengthening interoperability, FAIRness and sustainability of AI in European research. |
SIESTA - Secure Interactive Environments for SensiTive data Analytics (SIESTA)
Zabezpečené interaktívne prostredia pre analýzu citlivých údajov
| Duration: | 1. 1. 2024 - 31. 12. 2026 |
| Evidence number: | 101131957 |
| Program: | Horizont Európa |
| Project leader: | Ing. Tran Viet PhD. |
| Annotation: | The FAIR principles provide a framework for enabling proper access and reusability of scientific data, and implementing them is a key goal of the European Open Science Cloud (EOSC). However, providing access to sensitive or confidential data while preserving privacy/confidentiality and usability for researchers is still an open question. Existing solutions like safe rooms, safe pods, or data safe havens are often challenging for the development of reproducible research and seem counter-intuitive when dealing with open science and FAIR principles. The SIESTA project aims to provide a set of tools, services, and methodologies for the effective sharing of sensitive data in the EOSC, following a cloud-based model and approach. SIESTA will provide user-friendly tools with the aim of fostering the uptake of sensitive data sharing and processing in the EOSC. The project will deliver trusted cloud-based environments for the management and sharing of sensitive data that are built in a reproducible way, together with a set of services and tools to ease the secure sharing of sensitive data in the EOSC through state-of-the-art anonymization techniques. The overall objective is to enhance the EOSC Exchange services by delivering a set of cloud-based trusted environments for the analysis of sensitive data in the EOSC demonstrating the feasibility of the FAIR principles over them. |
National Projects
AI4CC - AI-Driven Self-awareness and Cognition for Compute Continuum (AI4CC)
Adaptívna a reflexívna umelá inteligencia pre výpočtové kontinuum
| Duration: | 1. 7. 2024 - 30. 6. 2027 |
| Evidence number: | APVV-23-0430 |
| Program: | APVV |
| Project leader: | doc. Ing. Hluchý Ladislav CSc. |
| Annotation: | AI4CC aims to contribute with new AI-based methods and algorithms to the development of modern computing continuums, addressing some of the key challenges of this domain. These challenges include enhancing the autonomy and self-adaptation capabilities of compute continuum platforms to optimize decision-making and responsiveness; adapting to changing conditions, necessitating flexible and adaptive computing models for dynamicity; efficiently managing vast amounts of data, considering factors like decentralization, scalability, and real-time processing for effective Data Management; ensuring transparency, explainability, and accountability in AI and machine learning models within compute continuums; achieving seamless interoperability between diverse devices and platforms within the continuum, impacting data exchange and communication for Interoperability, and dealing with resource heterogeneity—variability in computing resources across the continuum, including edge and cloud environments, posing challenges in optimizing performance and resource utilization. By systematically addressing these challenges and pioneering advancements in these key areas, AI4CC aims not only to bridge existing gaps but to propel compute continuums into a new era of efficiency, adaptability and security. The project envisions a future where compute continuums seamlessly integrate into various domains, fostering a holistic and intelligent computing environment that adapts to the ever-evolving demands of the digital landscape. |
CFD simulations of tunnel fire and wildland fire using FDS
CFD simulácie požiaru v tuneli a lesných požiaroch pomocou FDS
| Duration: | 17. 10. 2025 - 16. 10. 2026 |
| Evidence number: | p1561-25-3 |
| Program: | Iné projekty |
| Project leader: | Ing. Valášek Lukáš PhD. |
Decentralized artificial intelligence in a distributed virtualized computing environment.
Decentralizovaná umelá inteligencia v distribuovanom virtualizovanom výpočtovom prostredí.
| Duration: | 1. 1. 2026 - 31. 12. 2029 |
| Evidence number: | 2/0081/26 |
| Program: | VEGA |
| Project leader: | Mgr. Bobák Martin PhD. |
| Annotation: | Artificial Intelligence (AI) currently represents one of the main pillars of technological progress. From healthcare to industry, education, and other industrial and scientific sectors, AI offers revolutionary solutions that are fundamentally changing how we approach new challenges. A key aspect of innovation in this field is data, and its exponential growth brings significant challenges in terms of processing and security. Addressing the aforementioned issues cannot rely on a centralized approach. Therefore, the methodology we propose is based on the concepts of decentralized AI, including federated, distributed, and split learning, with trained models being multi-task and enabling multi-criteria optimization. This kind of concept has specific requirements for the software system, which must fully support the lifecycle not only of the AI itself but also of individual models. The research outcomes will contribute to the development of scalable and secure AI solutions in distributed environments. |
DyMAX - Dynamic malware analysis with explainable AI
Dynamická Malvérová Analýza s vysvetliteľnou AI
| Duration: | 1. 9. 2024 - 30. 6. 2028 |
| Evidence number: | DyMAX |
| Program: | APVV |
| Project leader: | Ing. Budinská Ivana PhD. |
| Annotation: | Machine learning allows processing large volumes of data and achieving high success rates in classification tasks in various areas, including malware analysis. The main disadvantage of many machine learning methods lies in their non-transparency: they are unable to provide human users with a comprehensible justification for their outputs. The field of explainable artificial intelligence (eXplainable AI – XAI) is currently very relevant, providing a number of new methods that allow overcoming this problem. Unfortunately, many XAI methods still do not reach the level of success and efficiency of traditional non-transparent machine learning. The aim of this project is to improve the usability of XAI in malware analysis by creating more sophisticated malware datasets based on dynamic malware analysis built on semantic representation, examining the most suitable XAI methods applicable in this context and their comparative analysis, and examining the possibilities of using symbolic outputs from XAI methods in distributed detection systems in combination with distributed consensus search algorithms. |
EnviroSens - Environmental sensors based on 2D nanomaterials
Environmentálne senzory na báze 2D nanomateriálov
| Duration: | 1. 8. 2024 - 31. 7. 2026 |
| Evidence number: | SK-BG-23-0017 |
| Program: | APVV |
| Project leader: | RNDr. Kostič Ivan |
| Annotation: | The objective of this project proposal is the research of new semiconducting 2D materials for application in environmental sensors. 2-dimensional (2D) materials have been at the forefront of materials research in recent years due to their unic electrical and optical properties and interesting mechanical properties deriving from their atomically thin dimensions. One of promising applications of 2D materials are chemical, environmental, and biological sensor devices based on such 2D materials. In this project, we will focus on the development of environmental sensors based on 2D materials with concentration on gas sensors. |
| Project web page: | https://www.ui.sav.sk/w/odd/senzor/projekty/ |
EXICOM - Experimental investigation and computer modelling of airflow during road tunnel fire
Experimentálne skúmanie a počítačové modelovanie prúdenia vzduchu pri požiari v cestnom tuneli
| Duration: | 1. 9. 2025 - 31. 8. 2029 |
| Evidence number: | APVV-24-0429 |
| Program: | APVV |
| Project leader: | Mgr. Weisenpacher Peter PhD. |
| Annotation: | The research project will contribute to the verification of the computer simulation of the airflow and smoke spread in road tunnels and to the increase of fire safety of tunnels in Slovakia. The project aim is to investigate the interaction of emergency ventilation operation, meteorological factors and fire in a real tunnel and to create a series of computer simulations of customer-designed fire scenarios in two motorway tunnels, which will be verified by in situ measurements. Detailed studies on the course of fires and the efficiency of emergency ventilation will be developed. The simulations will be carried out on the HPC infrastructure at the Slovak Academy of Sciences. In order to validate the results of the created simulations, full-scale experiments and measurements of airflow and meteorological factors will be carried out by the customer of the project results. Modifications to the Tunnel Traffic & Control Simulator (TTOS) at the University of Zilina in Zilina will be designed and implemented in accordance with current legislation, which will strengthen its uniqueness in the Central European area and improve its use for training and testing tunnel control operators in Slovakia. Part of the solution will be the recording and evaluation of emergency events in tunnels in Slovakia and the development of a series of visualizations of the course of fires based on computer simulations for TTOS, which will serve as a visualization didactic tool in the education of tunnel control operators and university students. The project solution will make it possible to intensify and streamline the research cooperation of the project solvers, to create a strong partnership of research organizations with important customers of the project results, and to effectively use the modern research infrastructure of the participating organizations to create innovative solutions to increase the safety of road tunnels. |
BioStimul - Experimental System for Wireless Stimulation and Monitoring of Selected Biological Properties and Cognitive Abilities of Drosophila melanogaster.
Experimentálny systém pre bezkontaktnú stimuláciu a monitorovanie vybraných biologických vlastností a kognitívnych schopností Drosophila melanogaster.
| Duration: | 1. 9. 2024 - 30. 6. 2027 |
| Evidence number: | APVV-23-0173 |
| Program: | APVV |
| Project leader: | Ing. Mgr. Andok Robert PhD. |
| Annotation: | The fruit fly Drosophila melanogaster serves as one of the most versatile models for studying human diseases, including neurodegenerative or learning disorders. Thanks to the unique genetic tools available exclusively in the fly model, Drosophila considerably contributed to discoveries of genetic regulations behind processes such as learning and behavior. Nevertheless, progress in this research area is limited by available technologies for the stimulation and tracking fruit flies. This project aims to develop novel equipment for wireless stimulation and monitoring of insect behavior. A wireless micro-heater will be installed onto the Drosophila’s body, designed and developed within this project, together with the microsensor of position / force. The fly will be stimulated individually under certain circumstances by locally controlled heat induced in the micro-heater realized by connecting a nanometric diamond film (as a supporting material bilogically compatible with the examined tiny insects, and at the same time a material with excellent thermal conductivity) with a high density micro coil consisting of a closed LC resonant circuit with a high-k dielectric material (ZrO2, SrTiO3, HfO2) used for the micro-capacitor. By exerting electromagnetic waves of certain resonant frequency related to the size of the coil, electromagnetic induction will occur and the device will heat up stimulating the insect. The project aims to optimize and utilize this technology for the study of olfactory and social learning. The technology will nonetheless have a broad impact in other areas of Drosophila neuroscience, ethology and physiology. The system can be, for example, used also for wireless stimulation of flies in various types of learning experiments, for tracking fly behavior in complex environments, or for studies of behavioral roles of diverse genes and environmental factors. The suggested technology will have broad implications in both primary research and biomedicine. |
Human-machine voice communication interface for non-standard and extreme use cases
Hlasové komunikačné rozhranie človek-stroj pre neštandardné a extrémne prípady využitia
| Duration: | 1. 1. 2025 - 31. 12. 2028 |
| Evidence number: | 2/0092/25 |
| Program: | VEGA |
| Project leader: | prof. Mgr. Beňuš Štefan PhD. |
| Annotation: | A voice interface for human-machine communication is an alternative to keyboard, touch or mouse interaction. Currently, voice interfaces are designed and tuned for "standard" use: communicating in a normal, calm, voice, mostly in a non-excited, announcing style, the target group is the majority of the economically active population, i.e. young and middle-aged adults. However, the research of non-standard, atypical, marginal and extreme cases of communication is gaining importance due to the increase in the robustness of a) formal models of the cognitive system of human-machine communication, as well as b) IT applications that use voice interfaces for wide target groups and communication situations. The presented project aims to research and optimize approaches to communication with seniors, pre-adolescent children, to affective communication (with high but also low emotional arousal), to communication with persons affected by neurodegenerative diseases, and to open the possibility of communication in Romani. |
Chemiresistive gas microsensors based on a combination of nanostructured transition metal sulfides and oxides
Chemoodporové mikrosenzory plynu na báze kombinácie nanoštrukturovaných sulfidov a oxidov prechodových kovov
| Duration: | 1. 1. 2025 - 31. 12. 2028 |
| Evidence number: | VEGA 1/1480/25 |
| Program: | VEGA |
| Project leader: | RNDr. Kostič Ivan |
| Annotation: | The project aims to conduct basic research in the field of discovering new, progressive semiconductor materials based on metal oxides and disulfides, as well as in the field of electrode material technology utilizing boron-doped diamond layers. We anticipate that our activities will focus on the preparation and investigation of the properties of TiO₂, NiO, and WS₂ layers, as well as their selected combinations and doping. These nanostructured semiconductor materials will be integrated into chemoresistive gas sensors placed on thin electro-insulating membranes. Attention will also be devoted to research into the technology of an integrated voltammetric sensor with a protective Nafion polymer layer for the simultaneous determination of trace concentrations of heavy metals. |
| Project web page: | https://ui.sav.sk/oddelenia/senzorickych-informacnych-systemov-a-technologii/projekty-oddelenia-senzorickych-informacnych-systemov-a-technologii/ |
SPICE - Smart Data PIpelines for the Cognitive ComputE Continuum (SPICE)
Inteligentné dátové kanály pre kognitívne výpočtové kontinuum
| Duration: | 1. 4. 2025 - 30. 9. 2027 |
| Evidence number: | 09I02-03-V01-00012/2025/VA/PZ |
| Program: | Plán obnovy EÚ |
| Project leader: | doc. Ing. Hluchý Ladislav CSc. |
| Annotation: | The growing scale and complexity of the Cloud led to the emergence of Edge and IoT computing in the "compute continuum" for applications relying heavily on sensor data and time-critical AI-assisted data processing. Its primary goal is to enable intelligent decision making and gain deeper insights across the continuum. At the same time, assembling and maintaining well-designed data pipelines involves addressing numerous technical, operational and organizational challenges. These hurdles and expertise/resource constraints act as a barrier for wider adoption of data pipelines. Our goal is to provide: (1) AI-assisted composition of smart data pipelines to radically simplify complex and distributed data processing, (2) a highly optimized execution environment and resource management that enable secure and smart data processing for the compute continuum. The results of our project will be made available as an innovation transformation incubator for others to exploit. |
Intelligent sensor systems and data processing
Inteligentné senzorové systémy a spracovanie dát
| Duration: | 1. 1. 2023 - 31. 12. 2026 |
| Evidence number: | VEGA 2/0135/23 |
| Program: | VEGA |
| Project leader: | Ing. Malík Peter PhD. |
| Annotation: | The central theme of Industry 4.0 and 5.0 is the digitization, intelligence and decentralization of management, so a key research is the new generation of smart sensors, able to cooperate and adapt to environment changes. This will be achieved by researching new methods of aggregating hyperspectral and multimodal data, as well as algorithms using artificial intelligence. The project is focused on intelligent algorithms for non-contact surface sensing in high-noise environments, which are able to learn the nature and noise distribution from data. This results in higher accuracy and greater noise robustness. The emphasis is on the classification and anomaly detection, which will bring more accurate and robust algorithms for use with the high noise content and long-tailed distribution that dominates in the common industrial environment. Research into aggregation algorithms for heterogeneous and multisensor data will bring new compensation mechanisms to suppress the effects of negative factors on sensor systems. |
Computer simulation of airflows and fire smoke spread in critical structures
Počítačová simulácia prúdenia vzduchu a šírenia dymu pri požiari v kritických objektoch
| Duration: | 1. 1. 2024 - 31. 12. 2027 |
| Evidence number: | VEGA 2/0096/24 |
| Program: | VEGA |
| Project leader: | Mgr. Weisenpacher Peter PhD. |
| Annotation: | Research in the proposed project is focused on formulation of new scientific knowledge on computer simulation of airflows and fire smoke spread in critical structures. Motorway tunnels were selected as the main subject of research interest based on discussions with specialists on fire safety in Slovakia. Tunnels belong to inteligent structures with high safety requirements due to potentially huge losses in case of fire. Natural airflows, airflows created by emergency ventilation, airflows induced by fire and fire smoke spread will be analyzed with focus on velocity fields, velocity profiles and smoke stratification. Computational aspects of efficient parallel realization of computer simulation on HPC systems will be investigated as well. The previous research results, experience and obtained experimental data will be utilized. The research is in line with current research trends and requirements of the fire researchers’ and simulators developers’ community and has potential to have significant social impact. |
REPRIKOM - Speech alignment for L2 communicative competence
Rečové prispôsobovanie sa a komunikatívne kompetencie v cudzom jazyku
| Duration: | 1. 9. 2024 - 30. 6. 2028 |
| Program: | APVV |
| Project leader: | prof. Mgr. Beňuš Štefan PhD. |
| Annotation: | Spoken interactions taking place in English as a non-native (L2) language are becoming a prevalent mode of dialogue in many spheres of professional discourse. Previous studies show that alignment among interlocutors during L1 interactions, i.e. their tendency to adjust their speaking behaviour to the interlocutor, correlates with multiple positive social aspects linked to the success of the interaction, rapport and engagement of the speakers, or their mutual evaluations in trust, attractiveness, or competence. Yet, due to the inherently complex nature of alignment stemming from multiple, potentially inter-relating factors affecting alignment, our understanding of the cognitive mechanisms and potential applicability in a language learning environment is limited. The proposed research aims at improving our understanding of key factors affecting alignment, such as the effect of native (L1) vs. non-native (L2) language, the relationship between non-verbal (e.g. intonation, speech rate) and verbal (syntactic structure, lexical choices) aspects of spoken interactions, the degree of L2 proficiency of the interlocutors, or their emotional and social state. Knowledge gained from a better understanding of the relationships between these factors and interpersonal alignment strategies generates testable predictions and hypotheses for applied research in which intervention approaches facilitating alignment might be proposed and tested for their hypothesized positive effect on the communicative competence in L2 interactions in both educational and professional settings. We aim to gain this knowledge by 1) creating a spoken corpus of semi-spontaneous dialogues in both L1 and L2 with a novel design varying the factors mentioned above, and 2) subsequently analysing the alignment strategies and the effect of these factors on the alignment behaviour of the interlocutors in the corpus. |
Next-Generation Gas Sensors Integrating Advanced 2D Materials and Neural Networks for Enhanced Detection of Gases in the Environment.
Senzory plynu novej generácie: Integrácia pokročilých 2D materiálov a neurónových sietí pre presnú detekciu plynov v bežných prevádzkových prostrediach.
| Duration: | 1. 1. 2026 - 31. 12. 2029 |
| Evidence number: | 2/0140/26 |
| Program: | VEGA |
| Project leader: | Ing. Mgr. Andok Robert PhD. |
| Annotation: | The project aims to conduct fundamental research in the field of gas sensors, focusing on the integration of advanced 2D materials using neural networks for better detection of reducing and oxidizing gases in common operating environments. The project implements knowledge on new advanced nanostructured semiconducting materials. It aims to investigate the properties of selected 2D nanostructured materials from the point of view of their application in microelectronics. We will focus on the application of mechanical and chemical exfoliation methods to layers of nanostructured disulfides (WSe, WS2, MoS2) and their transfer to a microelectronic element on a substrate. The results will be compared with other materials such as TiO2, NiO and their combinations. We will connect the selected gas sensors to a neural network, which will be trained on a large number of cases in order to identify a given detected gas and determine its concentration as accurately as possible. |
STICS - Smart transformation & Innovation Consortium Slovakia
Smart transformačné a inovačné konzorcium Slovensko
| Duration: | 1. 4. 2025 - 30. 9. 2027 |
| Evidence number: | 09I02-03-V01-00011 |
| Program: | Plán obnovy EÚ |
| Project leader: | Ing. Balogh Zoltán PhD. |
| Project web page: | https://stics.umb.sk/ |
AIHydroHUB - (AIHydroHUB)
Strategické partnerstvo pre výskum zelenej a udržateľnej energetiky s využitím umelej inteligencie pre významné vodné diela
| Duration: | 1. 1. 2026 - 31. 12. 2029 |
| Evidence number: | 401101C567 |
| Program: | Štrukturálne fondy EÚ Bratislavský kraj |
| Project leader: | doc. Ing. Hluchý Ladislav CSc. |
Supercomputer modeling of the properties of 2D nanomaterials using first-principle methods with the support of artificial intelligence: 2D-AIMAT
Superpočítačové modelovanie vlastnosti 2D nanomateriálov použitím prvoprincípových metód s podporou umelej inteligencie: 2D-AIMAT
| Duration: | 1. 1. 2025 - 31. 12. 2027 |
| Evidence number: | 2/0133/25 |
| Program: | VEGA |
| Project leader: | Mgr. Brndiar Ján PhD. |
Structures S3PR, ES3PR and S4PR of mathematical models of resource allocation in discrete production systems based on Petri nets and their use for deadlock prevention.
Štruktúry S3PR, ES3PR a S4PR matematických modelov alokácie zdrojov v diskrétnych výrobných systémoch na báze Petriho sietí a ich využitie na prevenciu deadlokov.
| Duration: | 1. 1. 2025 - 31. 12. 2028 |
| Evidence number: | 2/0005/25 |
| Program: | VEGA |
| Project leader: | doc. Ing. Čapkovič František CSc. |
| Annotation: | Discrete systems remain in a certain state until they are forced to change this state due to the occurrence of some discrete event. They are called DES (Discrete-Event Systems). They include a wide class of real systems – flexible (alias automated) manufacturing systems, robotic cells, communication systems, transport systems, etc. Petri nets PN are very suitable for mathematical modelling of DES. RAS (Resource Allocation Systems) in DES tend to deadlocks. PN-based DES models can be used to eliminate deadlocks. Three model paradigms, namely S3PR, ES3PR and S4PR, will be investigated using two approaches: (i) structural analysis of PN RAS models, specifically using siphons and traps, without the need to know the initial state, (ii) P-invariants PN models of RAS and reachability tree (RT) of states. Both approaches will be applied to all model paradigms, compared and evaluated using simulations in Matlab (or SciLAB). |
AFAROB - Therapy of Aphasia Using Social Robotics and Artificial Intelligence
Terapia afázie s využitím sociálnej robotiky a umelej inteligencie
| Duration: | 1. 3. 2025 - 30. 6. 2028 |
| Evidence number: | VV-MVP-24-0072 |
| Program: | APVV |
| Project leader: | Mgr. Čiernik Kevická Viktória PhD. |
| Annotation: | The project focuses on innovative approaches in aphasia therapy, specifically on the integration of social robotics and artificial intelligence into therapeutic procedures. Aphasia is a disorder of speech production and comprehension caused by brain damage, often as a result of stroke, which leads to serious communication problems and social isolation. Current therapeutic methods emphasize intensive and authentic communication, but this is not always possible due to limited access to speech therapy. The project has three main objectives: to design an innovative therapeutic approach at the level of discourse - spontaneous speech, to verify the usability of a social robot within the framework of the created therapeutic approach, and to verify the usability of large language models in therapy. The applicability of the therapeutic approach using social robotics and large language models is initially tested on a sample of healthy participants, and then on a sample of participants with aphasia. The result of the project is the evaluation of usability of a social robot and large language models in therapy in the clinical group of people with aphasia. The benefit of the project is its long term potential to increase the availability of therapy and the frequency of therapeutic sessions and to simulate the natural course of speech therapy, which contributes to the functionality of communication and to improving the quality of life of patients. |
INFOTICK - Getting the right info on ticks (INFOTICK)
Získanie pravdivých informácií o kliešťoch
| Duration: | 1. 7. 2023 - 30. 6. 2027 |
| Evidence number: | APVV-22-0372 |
| Program: | APVV |
| Project leader: | Ing. Gatial Emil PhD. |
| Annotation: | Despite the fact that the castor bean tick, Ixodes ricinus has been studied for a century, many questions regarding its ecology remains unanswered. Several aspects of its basic biology and phenology are still unexplored. Global changes, including climate shifts, transformation of the landscape and urbanization, contribute to the switch not only in tick distribution, but also in bionomics and seasonal activity of ticks. The ornate dog tick, Dermacentor reticulatus adapts quickly to changing conditions and its range is expanding. There is the need for detailed description of areas where these ticks are found (natural as well as urban habitats), since their ranges have changed during the last decades. The main risk factor for tick -exposed people in a given area is the density of infected questing ticks. In the proposed project, questing activity of ticks will be monitored using the tick -plot methodology „tick gardens“ in field plots as well as flagging the vegetation for questing ticks. Using the tick-plot methodology, we will also follow the tick life cycle and the seasonality of various developmental events (especially moulting) as well as the longevity of different life stages. Since these two species of ticks are considered epidemiologically the most important, we will also identify the prevalence and occurrence of both pathogen infected questing ticks and infected ticks feeding on animals. Furthermore, with changing conditions, the invasion and occurrence of „non-native“ species of ticks in Slovakia will be closely monitored since these emerging tick species can introduce new pathogens to our area. The information obtained by the research team during the project as well as during previous studies will be transferred and used in the development of a mobile application for tick identification and the creation of a website that will bring benefits to the general public and professionals to understand the risk of infection with the tick-borne pathogens. |
Projects total: 30