Contacts
Intranet
SK
International projects
| PhoBioS – Understanding interaction light – biological surfaces: possibility for new electronic materials and devices | |
| Pochopenie interakcie svetlo – biologické povrchy: možnosti pre nové elektronické materiály a zariadenia | |
| Program: | COST |
| Duration: | 19.10.2022 – 18.10.2026 |
| Project leader: | RNDr. Hain Miroslav, PhD. |
| Annotation: | It is known that various biological surfaces are covered with micro- and nano-structures that perform a variety of functions (e.g., anti-reflective, structural coloration, anti-fouling, pro- or anti-adhesion …) and inspire us to many industrial applications. In recent years, there has been a significant upsurge of research in this field. The main objective of the COST Action "Understanding light-biological surface interactions: opportunities for new electronic materials and devices" is to bring together scientists coming from different disciplines in this lively area of research, focusing on the photonic effects of nano- and micro-structures of biological surfaces and their bionic applications. The consortium will ensure cross-inspiration between participants coming from different research fields and foster research innovation and possible industrial development. |
| Project website: | https://www.cost.eu/actions/CA21159/ |
| ANTICIPATE – ANTICIPATE: extended-range multi-hazard predictions and early warnings | |
| ANTICIPATE: dlhodobé (rozšírené) predpovede viacerých typov rizík a včasné varovania | |
| Program: | COST |
| Duration: | 29.10.2025 – 28.10.2029 |
| Project leader: | Ing. Košta Radoslav |
| Annotation: | Operational extreme weather forecasts and early warnings are generally limited to timescales of up to around 10 days and to predicting single events, such as flooding or a heatwave. However, a new generation of experimental ‘extended-range’ weather predictions that extend up to 46 days have been developed over the last decade by the world’s leading meteorological centres. A key motivation of exploring this prediction timescale is to bridge the gap between timescales, incorporate the latest ‘multi-hazard’ approaches, and improve early warnings and anticipatory actions. Currently, however, the extended-range prediction and the multi-hazard communities are largely disconnected. To date, there has been no coordinated effort to build a network that connects these disciplines and communities towards the development of operational systems. However, it is essential that these communities come together to explore windows of opportunity and instigate a step-change in the way forecasts are designed, produced and used. To address this challenge, ANTICIPATE will create the first pan-European network focused on extended-range multi-hazard predictions and warnings. ANTICIPATE will bring together existing but largely disconnected disciplines, operational practitioners and stakeholders (including extreme weather forecasting, extended-range prediction and climate dynamics, disaster risk reduction, multi-hazards, and communications) to drive forward advancements in the science, training, communication and application that will support next generation of effective early warnings that enable preparedness and action across hazards and forecasting lead times. ANTICIPATE will provide vital leadership in multi-hazard predictions and warnings, address gaps and challenges, and educate the next generation of forecasters and communicators for societal benefit. |
| Project website: | https://www.cost.eu/actions/CA24144/ |
| MEDUSSE – Seasonal-to-decadal climate predictability in the Mediterranean: process understanding and services | |
| Sezónna až dekádová predpovedateľnosť klímy v Stredomorí: pochopenie procesov a implementácie | |
| Program: | COST |
| Duration: | 8.10.2024 – 7.10.2028 |
| Project leader: | RNDr. Krakovská Anna, CSc. |
| Annotation: | Climate forecasting has enormous potential influence in different socio-economic sectors, such as agriculture, health, water management, and energy. Actionable climate information is particularly relevant at seasonal-to-decadal timescales, where predictability is linked to slow fluctuations of the system such as those in the ocean, sea-ice and land-surface, thus bridging weather/sub-seasonal predictions (mainly relying on atmospheric initial condition) with future projections (mainly based on atmospheric radiative forcing). Seasonal-to-decadal climate forecasting has progressed considerably in recent years, but prediction skill over the Mediterranean is still limited. Better understanding the drivers of regional climate anomalies as well as exploring untapped sources of predictability constitute a much-needed and timely effort.Climate variability and change pose significant challenges to society worldwide. As a result, there is a growing demand to develop improved climate information products and outlooks to help decision making and sustainable development. This is particularly critical in the Mediterranean, a region sensible to natural hazards (e.g. droughts, floods) and vulnerable to climate stress (i.e. global warming). Such an improvement can only be achieved by coordinating efforts of research groups with different expertise and trans-disciplinary. In this Action, both the scientific challenge and societal challenge will be addressed by establishing a network of experts on climate variability, predictability, prediction and application. The Action will provide support to increase awareness and capability, and guidance to suitably evolve climate knowledge into services. Specific objectives include cross-cutting training and collaboration, empowering national hydro-meteorological agencies, and fostering a continuous communication between climate researchers and stakeholders. |
| DYNALIFE – Information, Coding, and Biological Function: the Dynamics of Life | |
| Informácia, kódovanie a biologická funkcia: Dynamika života | |
| Program: | COST |
| Duration: | 19.9.2022 – 18.9.2026 |
| Project leader: | RNDr. Krakovská Anna, CSc. |
| Annotation: | In the mid-twentieth century two new scientific disciplines emerged forcefully: molecular biology and information-communication theory. At the beginning cross-fertilisation was so deep that the term genetic code was universally accepted for describing the meaning of triplets of mRNA (codons) as amino acids.However, today, such synergy has not take advantage of the vertiginous advances in the two disciplines and presents more challenges than answers. These challenges are not only of great theoretical relevance but also represent unavoidable milestones for next generation biology: from personalized genetic therapy and diagnosis, to artificial life, to the production of biologically active proteins. Moreover, the matter is intimately connected to a paradigm shift needed in theoretical biology, pioneered long time ago in Europe, and that requires combined contributions from disciplines well outside the biological realm. The use of information as a conceptual metaphor needs to be turned into quantitative and predictive models that can be tested empirically and integrated in a unified view. The successful achievement of these tasks requires a wide multidisciplinary approach, and Europe is uniquely placed to construct a world leading network to address such an endeavour. The aim of this Action is to connect involved research groups throughout Europe into a strong network that promotes innovative and high-impact multi and inter-disciplinary research and, at the same time, to develop a strong dissemination activity aimed at breaking the communication barriers between disciplines, at forming young researchers, and at bringing the field closer to a broad general audience. |
| STOCHASTICA – Stochastic Differential Equations: Computation, Inference, Applications | |
| Stochastické diferenciálne rovnice: výpočty, inferencia, aplikácie | |
| Program: | COST |
| Duration: | 26.9.2025 – 25.9.2029 |
| Project leader: | MSc. Krakovská Hana |
| Annotation: | Stochastic differential equations (SDEs) are used to model phenomena under the influence of random noise and uncertainty and are useful in an extraordinary range of applications. In health, SDE models of tumour growth can help medical practitioners design interventions. In clean energy, they can model airflow around wind turbine blades, and enable multiscale modelling of entire wind farms and energy grids by representing small scale effects as noise. In computing, SDEs can be used to develop training algorithms for deep learning algorithms.The development and effective deployment of stochastic models requires input from a broad range of specialist experts: applied modellers, theoretical mathematicians, numerical analysts, and statisticians, all guided by the needs of stakeholders in academia and industry. However, in the current European research landscape, there is no large scale framework enabling these communities to interact, and opportunities for goal-driven research progress that is informed by all relevant expertise are being lost.Under the umbrella of computational stochastics, STOCHASTICA will bring together members of all of these communities to create a network of researchers with common goals informed by academic and industry partners. The work of the Action will generate a computational toolbox including a database of test problems, implementation guidance, and accessible descriptions of mathematical quality that empower non-specialist experts to make appropriate and routine use of stochastic models in applications such as natural resource management, renewable energy transmission, medical and public health applications including epidemiology and models of tumour growth. |
| Project website: | https://www.ucc.ie/en/stochastica/ |
| DONUT – European Doctoral Network for Neural Prostheses and Brain Research | |
| Európska doktorandská sieť pre neurálne protézy a výskum mozgu | |
| Program: | Horizont Európa |
| Duration: | 1.1.2024 – 31.12.2027 |
| Project leader: | Ing. Mgr. Rosipal Roman, DrSc. |
| Annotation: | DONUT, European Doctoral Network for Neural Prostheses and Brain Research has the mission to provide a multidisciplinary and inter-sectoral network for young talented researchers. The ambition of the project is to serve as a springboard for the expansion of EU partners into the fast-developing Brain-Computer Interface (BCI) technology and connected scientific disciplines. The DN will leverage the complementary expertise of 7 academic beneficiaries and 8 associated partners from 8 EU countries, to guide its 10 doctoral candidates (DCs) to address and solve deep problems in brain research, development of different BCI applications and systems with the latest technological advancements.The proposed DN will integrate existing research in BCI systems to make it more user-friendly, suitable for different types of potential end-users and for modern medical diagnostics. The DN would also provide excellent opportunities for career development of young researchers under the umbrella of German doctorate graduate school PK NRW (Graduate School for Applied Research in North Rhine-Westphalia, with over 180 participating professors), regularly offering specialised trainings and courses including Scientific Research Writing, Academic Presentation Skills, etc. Early scientific independence is one of key goals of training programmes.It is the ambition of DONUT to build a strong and lasting network not only between the DCs but also between the participating beneficiaries and associated partners. DONUT researchers will benefit of a dense network of contacts with scientists acquired during network-wide training events, to improve their career prospects in the European and worldwide innovation sector, having the opportunity to become scientists employable in both the industrial and academic sectors. The participation of 7 industrial participants in research and training programmes will guarantee extensive inter-sectoral experience for the trainees and maximise the impact. Project Partners:Rhine-Waal University of Applied Sciences (HSRW), GermanyRadboud University (RU), NetherlandsKatholieke Universiteit Leuven (“KU Leuven”) (KUL), BelgiumUniversidad Miguel Hernández de Elche (UMH), SpainAarhus University (AU), DenmarkKauno technologijos universitetas (KTU), LithuaniaInstitute of Measurement Science, Slovak Academy of Sciences (IMSAV), Slovakia |
| PREMEDICARE – Precision Medicine for Cardiac Arrest | |
| Presná medicína pri zástave srdca | |
| Program: | COST |
| Duration: | 13.10.2025 – 12.10.2029 |
| Project leader: | Ing. Švehlíková Jana, PhD. |
| Annotation: | Out of hospital cardiac arrest (OHCA) is a major health problem occurring in individuals of all sexes, ethnicities, and socioeconomic positions. OHCA is responsible for approximately one third of deaths in people aged under 50 years, yet our understanding of OHCA in this age group is sparse. Evidence suggests that inherited cardiac diseases underlie a significant proportion of OHCA cases in younger people, but we do not fully know the distribution of causes of OHCA which makes treatment and management of OHCA victims challenging. The PREMEDICARE Action brings together a multi-disciplinary group of experts to better understand the causes of OHCA and its long-term effects with the aim of facilitating the development and adoption of precision medicine strategies to alleviate the burden of OHCA in people under 50-years throughout Europe. Members of the PREMEDICARE network will work together to develop standardised procedures for better recording of data to enable identification of at-risk individuals across Europe, better understand geographical differences in the treatment of young OHCA patients and facilitate better management of long-term limitations linked to OHCA survival. The ultimate goal of the Action is to establish the tools and resources necessary to support the uptake and use of precision medicine approaches for the treatment and management of OHCA in the clinic. |
| Project website: | https://www.cost.eu/actions/CA24142 |
| AtheroNET – Network for implementing multiomic approaches in atherosclerotic cardiovascular disease prevention and research | |
| Sieť/zoskupenie pre implementáciu multiomického prístupu pri prevencii a výskume aterosklerotickej choroby srdca | |
| Program: | COST |
| Duration: | 17.7.2024 – 18.10.2026 |
| Project leader: | Ing. Švehlíková Jana, PhD. |
| Annotation: | AtheroNET aims to consolidate and connect experts from different fields into European and international network that will focus on the use of multiple omics technologies and data integration through machine learning/artificial intelligence approach to bring novel paradigms in prevention, diagnosis, and treatment of atherosclerotic cardiovascular disease. |
| Project website: | https://atheronet.eu/ |
| Precision Neuromodulation for Chronic Pain: Integrating Functional MRI and Focused Ultrasound for Personalised Treatment | |
| Presná neuromodulácia chronickej bolesti: Integrácia funkčnej magnetickej rezonancie a fokusovaného ultrazvuku pre personalizovanú liečbu, skratka „NeuroPain“ | |
| Program: | ERANET |
| Duration: | 1.1.2026 – 31.8.2028 |
| Project leader: | Doc. RNDr. Witkovský Viktor, CSc. |
National projects
| ReAcMap – Assessment of restitution of normal ventricular activation by ECG mapping | |
| Vyhodnotenie reštitúcie normálnej komorovej aktivácie pomocou EKG mapovania | |
| Program: | APVV |
| Duration: | 1.9.2025 – 31.8.2028 |
| Project leader: | Ing. Švehlíková Jana, PhD. |
| Annotation: | The project intends to optimize and personalize cardiac resynchronization therapy (CRT) for patients with heart failure. This effective, nonpharmacological, pacing-based treatment aims to restore interventricular resynchronization of ventricular activation by pacing both ventricles with an expected subsequent increase in cardiac output. However, about 30-40% of the patients do not benefit from the therapy and are designed as “non-responders”. To improve the efficacy of ventricular resynchronization, conduction system pacing (CSP) was recently introduced into clinical practice, which replaces biventricular stimulation with direct stimulation of the conduction system. However, CSP to achieve a narrow QRS complex is not feasible in up to 15% of patients for multiple anatomical, pathological, and technical reasons. Therefore, an optimal individualized strategy to achieve effective ventricular resynchronization is an unmet need in electrical therapies in heart failure patients. The proposed research project is methodologically based on noninvasive body surface potential ECG measurements of patients with heart failure indicated for a CRT/CSP device implantation. From the measured data, conducted using a dedicated in-house measuring device, the new parameters for the evaluation of the dynamics of the ventricular activation will be derived to set the proper programming stimulation of the device. A possible reduction of the number of ECG electrodes from the currently used 128 will also be studied to facilitate the routine clinical feasibility of the recording system. The simulations of the failing heart will be performed to understand better the processes that are undergoing in the ventricles. The area of the starting spontaneous ventricular activity will be assessed by solving the inverse problem of electrocardiography using a personalized heart-torso model obtained from the CT scan. The dedicated measuring system will implement a GUI to apply the suggested methods easily. |
| Project website: | https://www.um.sav.sk/reacmap/ |
| Multi-lead ECG measurement to create a personalized model of the electric field of the heart and research the possibilities of its use for the diagnosis and optimization of cardiac arrhythmia therapy | |
| Mnohozvodové meranie EKG na vytvorenie personalizovaného modelu elektrického poľa srdca a výskum možností jeho využitia na diagnostiku a optimalizáciu terapie srdcových arytmií | |
| Program: | VEGA |
| Duration: | 1.1.2025 – 31.12.2028 |
| Project leader: | Ing. Švehlíková Jana, PhD. |
| Annotation: | In the proposed project, we plan to link multi-lead ECG measurements on the chest with a personalized model of the heart and chest of the measured patient obtained from a CT scan. We intend to implement the physiological properties of healthy myocardium into the heart chamber model, as well as some pathological morphological and structural changes, such as left ventricular hypertrophy or left bundle branch block in heart failure. Using simulations of activation propagation in the heart chambers, we will study changes in ECG signals in the above diagnoses, as well as the consequences of different settings of supportive stimulation in resynchronization therapy for heart failure. We will implement advanced methods of signal processing and calculation of selected characteristics in quasi-real time into a new multi-lead ECG measurement system with wireless data transmission to a control computer. |
| VERISCAN – Metrological framework for the verification of dynamic 3D scanning systems according to ISO GPS in digital manufacturing | |
| Metrologický rámec verifikácie dynamických 3D skenovacích systémov podľa ISO GPS v podmienkach digitálnej výroby | |
| Program: | APVV |
| Duration: | 1.9.2026 – 31.8.2029 |
| Project leader: | Doc. RNDr. Witkovský Viktor, CSc. |
| Annotation: | The project addresses the lack of a comprehensive methodological framework for the verification of handheld 3D scanning systems. Despite their massive implementation in digital manufacturing (Industry 4.0/5.0), their metrological assurance lags behind technical hardware capabilities. The core scientific challenge is the missing link between the variable nature of handheld scanning (operator influence, trajectory, strategy) and the strict requirements of the Geometrical ProductSpecifications (ISO GPS) system.The objective is to research and develop a metrological framework that transforms handheld 3D scanning from avisualization tool into a full-fledged system for product conformity decision-making. The project focuses on developing specialized reference artifacts with complex geometry designed for dynamic optical systems. It uniquely combines the technological expertise of UNIZA in digital quality control with the fundamental metrological competencies of the Institute of Measurement SAS in calibration and uncertainty estimation (GUM).The original contribution is an ISO GPS-oriented verification methodology that systematically integrates dynamic measurement uncertainty sources into final conformity assessment. The outputs include a physical reference artifact with SI traceability and verified procedures for the automotive and machinery industries. The project directly supports digital manufacturing chains by enhancing production quality and reducing non-conformance costs through metrologically correctvalidation of complex components. |
| AgeFlex – Development and standardization of MR-based methods for detecting and evaluating metabolic and structural adaptations of aging muscles to exercise. | |
| Vývoj a štandardizácia MR metód založených na magnetickej rezonancii na detekciu a hodnotenie metabolických a štrukturálnych adaptácií starnúcich svalov na cvičenie. | |
| Program: | APVV |
| Duration: | 1.9.2025 – 31.8.2029 |
| Project leader: | Mgr. Klepochová Radka, PhD. |
| Annotation: | Aging is associated with a loss of muscle mass and the functional capacity of skeletal muscles; however, regular exercise can slow down these processes. The focus of this project is on examining the metabolic, functional, and structural parameters in the lower limb muscles, which we can non-invasively and repeatedly measure using innovative magnetic resonance methods (MR). This allows us to compare the trajectories of aging in skeletal muscles of sedentary individuals and those who are physically active. One of the key parameters that define a muscle\’s ability to efficiently mobilize and use energy for muscle work is called metabolic flexibility. The aim of the project is to develop innovative MR methods to study metabolic flexibility and structural changes in skeletal muscles during aging, and relate them to whole-body metabolic flexibility, as well as the metabolic phenotype and structural and molecular changes in the skeletal muscles of older adults. As part of the project, we will standardize the measurement of dynamic changes in metabolites in muscle during exercise using proton (1H) MR spectroscopy, create standard procedures for quality control of acquired MR spectroscopy data, and a key aspect of the project will also be the development of an automated segmentation method based on a convolutional neural network, which will enable more efficient and reliable evaluation of MR images of skeletal muscles. These innovative methods will be validated using data from ongoing longitudinal studies at the Biomedical Center of the Slovak Academy of Sciences, and their results will be directly compared with parallel changes in metabolic health, functional capacity, histological structure, and molecular mediators of metabolic flexibility in skeletal muscles. The results may not only improve our understanding of the processes that define metabolic flexibility during aging but may also offer relevant strategies to support metabolically healthy aging. |
| VAC-YAG – Research on the influence of hydrodynamic flows on the distribution of oxygen vacancies in Yttrium-Aluminum garnet single crystal grown via Horizontally Directed Crystallization for detectors | |
| Výskum vplyvu hydrodynamických prúdov na rozloženie kyslíkových vakancií v monokryštáloch ytriovo-hlinitého granátu vypestovaných horizontálne riadenou kryštalizáciou pre detektory | |
| Program: | APVV |
| Duration: | 1.9.2026 – 31.8.2029 |
| Project leader: | Ing. Majerová Melinda, PhD. |
| Annotation: | The project is focused on the research of oxygen vacancies in single crystals of Yttrium aluminium garnet. During the growing process, these oxygen vacancies are distributed unevenly in the volume of the crystal, which is affected by hydrodynamic flows in the melt. Since the melting temperature for YAG is higher than 1950°C, a physical model will be built for the research. On the basis of these data, an experimental thermal unit will be assembled with the possibility of controlling the thermal field, which will enable the control of convection currents in the melt. Crystals will be grown in thisthermal unit and will be characterised. The result of the project will be data and correlation of the influence of hydrodynamic flows on the distribution of oxygen vacancies in single crystal of Yttrium aluminium garnet, which has a high potential for use in detectors. |
| MRCartilage – Automatic data evaluation tool from the longitudinal quantitative MRI studies of articular cartilage | |
| Automatický softvérový nástroj na výhodnocovanie kvantitatívnych MRI štúdií artikulárných chrupaviek v čase | |
| Program: | APVV |
| Duration: | 1.7.2022 – 30.6.2026 |
| Project leader: | Ing. Dr. Szomolányi Pavol, (PhD.) |
| Annotation: | The aim of the project is to design a comprehensive tool for automatic evaluation of human articular cartilage data from quantitative MRI. Data obtained from the Osteoarthritis Initiative database, and measured at Institute of Measurement Science and Medical University of Vienna will be segmented using an automated segmentation tool based on convolutional neural networks. The annotated data will then be registered on quantitative MRI data that will be available from the database (T2 and T1rho mapping, gagCEST, sodium MR) using automated or semiautomated tools developed within this project. The data obtained will be evaluated at multiple time points according to MR measurements that will be available. In addition to quantitative MR data, this will include volumetric data, cartilage thickness, and texture analysis of quantitative maps. Patient evaluation will be based on risk factor groups (transverse ligament rupture, meniscus rupture and menisectomy). The expected number of patients is approximately 4000 divided into individual groups in the ratio 40/30/30. The output of the project will be a compiled version of an automatic cartilage evaluation tool that will be available in a public source (such as website of Institute of Measurement). |
| CARE-BCI – Cooperative AI-enhanced BCI-HMD rehabilitation for post-stroke recovery | |
| Kooperatívna AI BCI-HMD rehabilitácia pre pacientov po cievnej mozgovej príhode | |
| Program: | APVV |
| Duration: | 1.9.2026 – 31.8.2030 |
| Project leader: | Ing. Mgr. Rosipal Roman, DrSc. |
| Annotation: | This project aims to advance post-stroke neurorehabilitation through the development of an artificial intelligence (AI)-enhanced, collaborative brain–computer interface (BCI) system integrated with immersive head-mounted display (HMD)–based virtual reality (VR). AI serves as a central enabling component, supporting adaptive neural decoding, cognitive-state monitoring, and data-driven optimization of rehabilitation protocols. A key focus is on the creation ofcooperative, shared-action rehabilitation environments, in which the patient and therapist jointly perform the same task in real time. This combination of AI-driven adaptation and shared-action cooperation moves beyond isolated task execution toward socially interactive, coordinated motor rehabilitation with high ecological validity.The approach extends the state of the art by employing AI for adaptive neural decoding, cognitive-state monitoring, and longitudinal meta-analysis of rehabilitation trajectories. Active BCI components use personalized models to decode motor imagery under inter- and intra-subject variability, while passive BCI continuously monitors cognitive workload, mentalfatigue, and engagement. An exploratory component investigates the feasibility of an AI-assisted therapeutic agent capable of partially supporting therapist actions within immersive, cooperative VR environments, while preserving safety, interpretability, and clinical oversight.The ambition is to establish a scalable and personalized neurorehabilitation framework that enhances therapeutic efficacy, strengthens patient–therapist interaction through shared-action VR tasks, and reduces therapist workload. By integrating active and passive BCI, cooperative VR, and explainable AI within a single coherent system, the project aims to generatenew scientific insights into rehabilitation dynamics and provide a clinically relevant pathway toward accessible, data-driven post-stroke rehabilitation in clinical and home-based settings. |
| DUOFLUOR – Dual‑tuned ¹H/¹⁹F RF coil for preclinical MRI | |
| Duálne ladená ¹H/¹⁹F RF cievka pre predklinické MRI | |
| Program: | APVV |
| Duration: | 1.9.2026 – 31.8.2030 |
| Project leader: | Ing. Gogola Daniel, PhD. |
| Annotation: | The project focuses on the design, optimization, and experimental verification of a dual‑tuned ¹H/¹⁹F radiofrequency (RF) coil intended for preclinical MRI. Combined ¹H/¹⁹F imaging represents a promising technology enabling simultaneousanatomical (¹H) and quantitative functional measurements (¹⁹F), particularly in studies involving the biodistribution offluorinated compounds, cell‑tracking applications, inflammatory processes, and functional lung imaging. The absence of endogenous ¹⁹F signal in biological tissues allows absolute quantification without background reconstruction, which increases the accuracy and interpretability of measurements. Despite its potential, only a limited number of solutions optimized for small‑animal imaging currently exist, and available systems often do not achieve the required sensitivity and B₁ homogeneity for fluorine MRI.The project includes the development of detailed FEM/FDTD models of various coil geometries, their optimization for bothresonance frequencies, and the subsequent construction of a physical prototype. The experimental phase will involveS‑parameter and Q‑factor measurements, B₁ field mapping, and testing of tuning stability. The functional performance ofthe coil will be evaluated using phantoms with defined fluorine content and, in the final stage, through preclinical measurements in small animals. The project also includes the development of a software tool that enables the calculationand optimization of RF coil parameters for different dimensions and frequencies.The outcome of the project will be an experimentally validated dual‑tuned ¹H/¹⁹F RF coil and a complete methodology forits design, applicable in preclinical research, pharmacological studies, and the development of fluorinated markers. Theproject will contribute to the advancement of preclinical MRI technologies in Slovakia and create a foundation for furtherinterdisciplinary applications in biomedical imaging. |
| TRACE-DC – Non-invasive measurement and metrological traceability of DC component in modern networks with battery storage | |
| Neinvazívne meranie a metrologická sledovateľnosť jednosmernej zložky v moderných sieťach s batériovými úložiskami | |
| Program: | APVV |
| Duration: | 1.9.2026 – 28.2.2029 |
| Project leader: | Ing. Gogola Daniel, PhD. |
| Annotation: | In the context of Slovakia\’s energy transformation, the share of renewable energy sources and battery storage systems integrated into the electricity grid is increasing. These devices operate with direct current (DC) but connect to alternating current (AC) networks, requiring metrologically reliable on-site measurement of DC power and energy. The first objective is to test and characterize a non-invasive DC sensor for measuring high currents (up to 1200 A) with 0.1% accuracy, suitable for battery storage, photovoltaic systems, and electric mobility. The second objective is to establish a reference standard for DC power and energy traceable to national standards. Additionally, connecting DC sources without transformers injectsDC components into AC networks, causing overheating, increased losses, and reduced power quality. The project therefore investigates the impact of DC components on AC electricity meters, with results serving as a basis for updating legislative requirements. The project supports the development of smart energy grids and contributes to effective electricity flow management in Slovakia\’s economy. |
| FERINO – Advanced diagnostics of neurodegenerative disorders using magnetic resonance techniques and artificial intelligence | |
| Pokročilá diagnostika neurodegeneratívnych ochorení pomocou techník magnetickej rezonancie a umelej inteligencie | |
| Program: | APVV |
| Duration: | 1.7.2023 – 30.6.2027 |
| Project leader: | Ing. Gogola Daniel, PhD. |
| Annotation: | Neurodegenerative diseases (ND) are becoming a severe problem in developed countries. Since we currently haveno effective therapies available, early diagnosis is critical to ensure a good quality of life for ND patients. ND arecharacterized by iron accumulation and magnetite mineralization in brain tissue, with ferritin as a precursor. Due toits low relaxivity, physiological ferritin is at the edge of visibility using magnetic resonance imaging (MRI)techniques. On the contrary, "pathological" ferritin causes a significant shortening of MRI relaxation times. Thiscreates hypointense artifacts, which theoretically allow the distinguishability of both proteins. Since ironaccumulation precedes the clinical symptoms of the disease, MRI has the potential to become a non -invasivediagnostic method for the early stages of ND. At present, however, this is limited by the insufficient characterizationof the relaxation properties of biogenic iron and the uncertainty in the interpretation of clinical data. Therefore, ourbasic goal (application output) is the development of a comprehensive methodology (FERINO software tool) for theunequivocal diagnosis of the early stages of ND. To reach our goal, we will use a combination of several diagnostictechniques and artificial intelligence tools. The diagnostic techniques include in-vitro, in-silico, and in-vivocharacteristics of ferritin relaxation, structural MRI, magnetic resonance spectroscopy (MRS), neurological tests,and clinical biochemistry biomarkers. The cornerstone of the methodology will be the FerroQuant software tool,which was proposed by the principal investigator within the APVV 2012. It enables the analysis and quantificationof iron-related clinical MRI data but lacks new findings in iron MRI (false-positive artifacts, ferritin\’s mineral phases).FerroQuant also does not use artificial intelligence and does not combine different diagnostic data, whic h, however,will be an integral part of the FERINO tool. |
| QuantMR – Optimization and Standardization of Quantitative Magnetic Resonance Imaging Methods. Suppression of Metallic Artifacts on low-field MR Scanners | |
| Optimalizácia a štandardizácia kvantitatívnych metód zobrazovania magnetickou rezonanciou. Potlačenie kovových artefaktov na nízkopolových MR skeneroch | |
| Program: | Plán obnovy EÚ |
| Duration: | 1.9.2024 – 31.8.2026 |
| Project leader: | Ing. Gogola Daniel, PhD. |
| CICPE – Cockroaches in complex past ecosystems | |
| Šváby v komplexných pravekých ekosystémoch | |
| Program: | APVV |
| Duration: | 1.9.2026 – 31.8.2028 |
| Project leader: | RNDr. Hain Miroslav, PhD. |
| Annotation: | Cockroaches, together with their predatory descendants, praying mantises, and social themes, have been pillars ofecosystems for more than 300 million years, primarily through the decomposition of biomass – they have no substitutes in this. New discoveries make it possible to grasp their evolution in a broader context and to the extent to which they influence the cycle of individual elements during the geological scale. Therefore, the samples in this project, in addition to the detailed frontier evolutionary analysis, also include complex geological, physical and chemical analysis and knowledge applied to entire ecosystems. The project benefits from global cooperation and possibly already processed material from around the world, which will represent not only almost 10% of the latest knowledge, but all groups are already included inthe appropriate system. Such work has no parallel in other terrestrial groups and is based on 110,000 samples, of which 4,000 are represented by various ambers, including those from the time of dinosaurs. This year\’s research has already been published in high impact (NSR IF= 20.7) and therefore this study is promising. In addition to science and wide popularization (over 40,000 students), the project will also create a new job and provide part-time jobs for exceptionally talented high school students who would otherwise end up abroad and/or in a commerce. |
| ARAM – Research of reference standards and measurement methods ensuring determination of the relationship of geometric specifications and qualitative indicators of 3D objects created by additive technologies | |
| Výskum referenčného etalónu a meracích metód zabezpečujúcich určenie vzťahu geometrických špecifikácií a kvalitatívnych ukazovateľov 3D objektov vytvorených aditívnymi technológiami | |
| Program: | APVV |
| Duration: | 1.7.2024 – 31.12.2027 |
| Project leader: | RNDr. Hain Miroslav, PhD. |
| Annotation: | The present project is aimed at evaluating the quality of additive manufacturing, a reference test artefact designed and developed for this purpose. The development of the reference artefact and the quantification of its parameters will make use of the latest knowledge in additive manufacturing, state-of-the-art measurement strategies implemented using X-ray microtomography, magnetometry, coordinate measuring devices, optical and electron scanning microscopes and methods of mathematical-statistical processing of measured data. Additive manufacturing technologies are capable of producing parts with very complex geometries that conform to the desired design without further machining. It is for this reason that they are very promising and their use in industry is growing. In order for additive manufacturing products to fully replace conventionally machined parts, they must meet the required quality criteria such as shape and dimensional accuracy, surface roughness, internal defects, residual stresses, etc. The final quality of parts produced by additive manufacturing technology is influenced by the characteristics of the raw material and the parameters and settings of the system. The aim of the project is to investigate the production of modified monofilaments and the measurement methods necessary for the realization of a stable and reproducible reference test artifact, which would be used to assess not only the geometric capability of additive manufacturing systems but also the internal structure and selected properties of the final product. |
| METIM – Design of a Methodology and its Verification for the Measurement of Selected Parameters of Ti Implants in the Manufacturing Process | |
| Návrh metodiky a jej overenie pre meranie vybraných parametrov Ti implantátov vo výrobnom procese | |
| Program: | APVV |
| Duration: | 1.7.2023 – 30.6.2027 |
| Project leader: | RNDr. Hain Miroslav, PhD. |
| Annotation: | The project focuses on the development and application of measurement and non-destructive testing methods inthe manufacturing of titanium dental implants. Dental implants are medical devices that have to comply with thetechnical requirements given by regulation of the European Parliament and Council EU 2017/745 from 5 Apr 2017.Under this regulation, among other obligations, the manufacturer must ensure that these devices are safe andeffective and do not compromise the clinical condition or patients safety. The dental implants should also meet ahigh level of health and safety protection, taking into account the generally accepted state of the art in science andtechnology. In this project we will address the requirements related to the design and manufacturing and inparticular: the compatibility of the different parts of the device, the influence of processes on the properti es of thematerials, the mechanical properties of the materials used such as strength, ductility, resistance to wear andfatigue, the properties of the surfaces, and confirmation that the device meets all defined physical specifications aswell as the identification of contaminants in the manufacturing process. To ensure these requirements, we intend touse state-of-the-art measurement methods such as X-ray microtomography (microCT), scanning electronmicroscopy (SEM), optical measurement of surface roughness, SQUID magnetometry. Since the abovemeasurement methods are time consuming and do not allow their full application in the production, the solution willalso include the design of effective methods of statistical quality control, which will be applied at the manufacturerof dental titanium implants MARTIKAN, s.r.o. The objectives of the proposed project correlate with the Researchand Innovation Strategy for Smart Specialisation of the Slovak Republic 2021-2027 (SK RIS3 2021+), while theyaffect two defined domains, namely Innovative Industry for the 21st Century and Healthy Society. |
| Changes in fossil lizard communities at older and younger Cenozoic sites in and around Europe as a result of dramatic global climate change – the key to understanding our future is in the past | |
| Zmeny v spoločenstvách fosílnych jašterov na lokalitách staršieho a mladšieho kenozoika v Európe a okolí ako dôsledok dramatických globálnych klimatických zmien – kľúčom k budúcnosti je chápanie minulosti | |
| Program: | VEGA |
| Duration: | 1.1.2024 – 31.12.2026 |
| Project leader: | RNDr. Hain Miroslav, PhD. |
| Annotation: | Terrestrial ecosystems in Europe, but practically everywhere, changed significantly during the Cenozoic due toglobal climatic changes. The importance of their better understanding is magnified by present global climatechange. In that respect, lizards are widely regarded as excellent indicators of past climates, particularly ambienttemperatures. The project is focused on the research of new, often complete finds from localities of different agessuch as the Paleocene site of Walbeck in Germany, the Lower Eocene sites of Dormaal in Belgium, Cos,Pasturat and Viélase in France. We also include new complete finds from the Middle Eocene German Messellocality (Unesco). Furthermore, fossils from the Oligocene and Lower Miocene sites of Phosphorites du Quercy(France), Miocene to Pliocene sites in Austria, Slovakia, Poland, Hungary, but also in Africa (Kenya) will bestudied. The aim is this research using CT is an interpretation of the phylogenetic relationships of studied taxaand changes in their communities. |
| DigiDent – Research of Dental Implant Components for the Creation of Personalized 3D Models | |
| Výskum digitalizácie komponentov dentálnych implantátov za účelom | |
| Program: | Plán obnovy EÚ |
| Duration: | 1.4.2024 – 30.6.2026 |
| Project leader: | RNDr. Hain Miroslav, PhD. |
| Annotation: | The main objective of the present project is the development and optimization of digitization methods and processes in the field of dental implants, with special emphasis on the development of personalized 3D models implementable in the production process. This goal includes the intention to expand current knowledge with new methodologies, technologies, and procedures that will enable more accurate, faster, and more efficient production of dental implants, with a high degree of individualization for individual patients.The fulfilment of the project\’s intentions should bring significant progressive changes in the field of digitization of dental implantology. This ambitious endeavor includes research-oriented research in digital technologies, data measurement, and processing to push the existing frontiers of knowledge and set new standards in the industry. Current knowledge will be expanded to include new methodologies, technologies, and procedures that have the potential to change the paradigm of the design, manufacture, and testing of dental implants. With new scientific findings and technological innovations, we can achieve the production of dental implants that will be more accurate, reliable, and effective in terms of their functional properties.A great benefit of the project is the high degree of individualization. By creating personalized 3D models, it will be possible to create implants tailored to individual patients. This will affect not only the implants themselves, but also the entire production process, from planning and design to final implementation. This will bring patients not only better quality treatment but also faster rehabilitation and a significant improvement in their quality of life.The result of the project will be not only technological progress in the design and production of dental implants but also innovative solutions with a positive overlap in the areas of healthcare and dentistry. The future development of dental implants will be based on accurate data and personalized solutions, which will increase the efficiency of the implantation process, safety, and patient satisfaction, and this is an important benefit of the presented project. |
| CAUSMET – Methods and algorithms for causal analysis and quantification of measurement uncertainty | |
| Názov projektu Metódy a algoritmy kauzálnej analýzy a kvantifikácie neistôt meraní | |
| Program: | APVV |
| Duration: | 1.9.2026 – 31.12.2029 |
| Project leader: | Doc. RNDr. Witkovský Viktor, CSc. |
| Annotation: | The project develops advanced methods and algorithms for causal analysis of stochastic and deterministic processes and for quantifying measurement uncertainties. It addresses methodological challenges in the analysis of time series and dynamical data, where correlation alone is insufficient to reveal the mechanisms governing system behavior. Manyapplications, therefore, require identifying causal relations between variables while reliably characterizing uncertainties arising from measurement processes, noise, and incomplete observations.The project will develop classical and modern approaches to causal analysis of time series based on probabilistic and statistical modeling, and integrate them with algorithms enabling statistical inference and prediction in the presence of randomness, measurement errors, and uncertainty.Modern applications in physical, biomedical, economic, environmental, and linguistic measurements, as well as in the social sciences (education, psychology), generate large and complex datasets with intricate dependence structures and temporal dynamics. A significant project component is hence the study of stochastic dynamical models, including diffusion processes, as a natural framework for modeling random dynamics observed via measurement time series. When modeling complex temporal or spatio-temporal data using kriging, causal structure will serve as a key starting point.The project also advances uncertainty methods for quantifying measurement uncertainties in line with modern metrology and aims to establish a unified methodological framework combining causal analysis, dynamical modeling, and statistical inference and forecasting. Interdisciplinary collaboration among the Institute of Measurement Science of the SAS, theMathematical Institute of the SAS, and the Faculty of Science of P. J. Šafárik University creates favorable conditions for the development of new theoretical results, efficient algorithms, and their applications. |
| EPISTATE – Gemcitabine-induced epigenetic states as predictors of treatment response in pancreatic cancer | |
| Epigenetické stavy indukované gemcitabínom ako prediktory odpovede na liečbu pri rakovine pankreasu | |
| Program: | APVV |
| Duration: | 1.9.2026 – 31.8.2030 |
| Project leader: | Ing. Maková Marianna, PhD. |
| Annotation: | Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest cancer types, with very limited treatment options andpoor long-term survival. Gemcitabine remains a cornerstone of PDAC therapy, yet most patients relapse because a fractionof tumor cells survives treatment and adapts. Understanding how these surviving cells persist is essential for improvingpatient outcomes.This project is based on the idea that gemcitabine does more than simply eliminate sensitive cancer cells. We propose thattreatment actively induces a stress-adaptive cellular state that allows tumor cells to survive without acquiring new geneticmutations. Importantly, this adaptive state is maintained by epigenetic mechanisms that control gene activity withoutchanging the DNA sequence. While these mechanisms help cancer cells survive chemotherapy, they may also create newweaknesses that can be therapeutically targeted.Our goal is to identify gemcitabine-induced epigenetic vulnerabilities and to define molecular signatures that indicate whentumors are susceptible to specific combination therapies. We will combine controlled gemcitabine treatment with modernsingle-cell technologies to precisely define adaptive tumor cell states. Using carefully selected epigenetic inhibitors andCRISPR-based genetic tools, we will determine which epigenetic regulators become essential for cancer cell survival afterchemotherapy. These findings will be validated in patient-derived tumor models and human tissue samples to ensureclinical relevance.By focusing on therapy-induced tumor cell adaptation rather than fixed genetic alterations, this project introduces a new,state-based framework for combination treatment in PDAC. The expected outcomes include the identification of epigeneticregulator classes linked to adaptive survival and the definition of molecular signatures that reflect tumor heterogeneity andprovide a biological foundation for the future development of rational therapeutic strategies. |
| The application of Artificial Intelligence methods for improved Magnetic Resonance Imaging | |
| Použitie metód umelej inteligencie na zlepšenie zobrazovania pomocou magnetickej rezonancie | |
| Program: | VEGA |
| Duration: | 1.1.2026 – 31.12.2028 |
| Project leader: | RNDr. Krafčík Andrej, PhD. |
| Annotation: | Magnetic Resonance (MR) is a widely used, useful diagnostic tool. However, since the measured signal isinfluenced by many factors (e.g., by the amount of biogenic contrast agents), quantitative analysis is difficult andlengthy. Therefore, the proposed project aims to model the influence of biogenic nanoparticles of ferritin on MRsignal and to use artificial intelligence for automated analysis (identification, segmentation and volumetry) ofstructures in MR images of joint, muscles and the heart. Advanced deep learning methods will be used for thesetasks. In addition, the project will focus on design and implementation of novel acquisition and calibrationsequences and protocols for metabolic and structural MR imaging. The project will also analyse the physiologicalresponse of MR measurements on cardiovascular system through wearable optical sensors. |
| OrgPipeSK2025 – Research of the metal organ pipe collections of historical pipe organs in Slovakia | |
| Výskum kovového píšťalového fondu historických organov na Slovensku | |
| Program: | APVV |
| Duration: | 1.9.2025 – 31.8.2028 |
| Project leader: | RNDr. Krafčík Andrej, PhD. |
| Annotation: | The sound-stylistic quality of historical organs is determined by various factors, including the material used for the organ pipes and the scaling (mensuration) of individual pipes and entire stops. The proposed project will examine organ metal as a key sound-stylistic determinant of historical organs, with consideration of the constructional evolution of organs in Slovakia from the 17th to the 20th century. The project will be conducted in four phases. The first phase will focus on the chemical composition analysis of organ pipe metal from selected instruments. These pipes and entire stops will undergo mensuration analysis, leading to the development of a mathematical model. The next phase will involve the visual recording (collection) of signings—etched or stamped markings indicating the specific tone for which a pipe is constructed. The signings of pipes from instruments with known builders will be documented to create a standard that will enable the use of neural networks (AI) to identify the authorship of organs whose builders are currently unknown. The research will also address the technical condition of organ metal, particularly corrosion, which affects not only the sound properties but also the preservation of the metal components of these historical instruments. The project\’s outcomes will include an online map of organ metal composition, corrosion, mensurations, an atlas of various types of corrosion and defects in organ pipes, as well as a comprehensive mapping of the metal and mensurations of studied stops. Furthermore, we will establish a method for gradually authorizing organs whose builders remain unidentified. All findings will be contextualized within the sound-stylistic development of historical organ building on Slovak territory. |
| Innovative approaches to uncovering relationships and interactions within multivariate time measurements | |
| Inovatívne prístupy k odhaľovaniu vzťahov a interakcií v rámci multivariátnych časových meraní | |
| Program: | VEGA |
| Duration: | 1.1.2026 – 31.12.2029 |
| Project leader: | RNDr. Krakovská Anna, CSc. |
| Annotation: | The project focuses on developing and applying methods for analyzing relationships between simultaneouslymeasured processes. After experience with bivariate causal detection, we now target multivariate cases, oftenmodelled as dynamical networks with time series at their nodes.We investigate Granger causality for autoregressive (AR) models and search for connections in reconstructedstate spaces when deterministic dynamics prevail. Transfer entropy, a strong representative of causal methods,will also be explored, including proposed modifications using alternative entropy measures. We also examine thepotential of machine learning methods in causal analysis.Expected outcomes include computational tools for more reliable detection of causal links and synchronisation,and for improved modelling, forecasting, and classification of the studied processes.The proposed methods will be validated on simulated data and applied to real measurements, such as effectivebrain connectivity and climate observations. |
| Development of advanced luminescent glass 3D structures by additive techniques | |
| Vývoj pokročilých luminscenčných 3D štruktúr pomocou aditívnej výroby | |
| Program: | VEGA |
| Duration: | 1.1.2024 – 31.12.2027 |
| Project leader: | Ing. Majerová Melinda, PhD. |
| ITAGES – Identification of stress-induced alterations in expression of NRF2 target genes in rat models of prehypertension: the effect of comorbid hypertriglyceridemia and dimethyl fumarate treatment | |
| Identifikácia stresom vyvolaných zmien v expresii cieľových génov NRF2 v potkaních modeloch prehypertenzie: vplyv komorbidnej hypertriglyceridémie a liečby dimetylfumarátom | |
| Program: | APVV |
| Duration: | 1.7.2023 – 30.6.2027 |
| Project leader: | Ing. Maňka Ján, CSc. |
| Annotation: | The nuclear transcription factor erythroid 2-related factor 2 (NRF2) is a key molecular link between several non-communicable diseases, as it regulates the expression of approximately 250 target genes, including those involvedin maintenance of redox balance, the development of metabolic disorders, cardiovascular and liver diseases, aswell as in immune responses. Borderline elevated blood pressure (prehypertension) is a common cardiovasculardisorder in humans, and elevated blood pressure has been found to be positively correlated with triglyceride levels.In addition, chronic stress is an etiological factor in the development of non-communicable diseases, includingelevated blood pressure and hypertriglyceridemia (HTG). In experimental studies, borderline hypertensive rats(BHR) and hypertriglyceridemic rats (HTGR) are suitable models of prehypertension without and with comorbidhypertriglyceridemia. These models are relevant for investigating the effects of stress as well as for investigatingthe role of changes in expression of NRF2 target genes in the development of hypertension associated withmetabolic diseases. To understand better the role of NFR2 as well as the impact of chronic social stress on thementioned diseased states, the aims of this project are: 1) to identify differences in expression of NRF2 targetgenes in two experimental models of prehypertension – without (in BHR) and with (in HTGR) comorbid HTG – incontrol conditions and during chronic social stress, 2) to determine if NRF2 activator dimethyl fumarate can reducestress-induced pathologies in prehypertensive rats, especially in those with comorbid HTG, and 3) to specify a setof suitable whole blood RNA biomarkers for evaluation of changes in NRF2 target genes in prehypertension andHTG and those genes altered by chronic social stress. |
| Innovations in the Transfer Entropy Method: Implementing Alternative Entropic Measures for More Robust Causal Inference | |
| Inovácie v metóde prenosovej entropie: Implementácia alternatívnych entropických mier pre robustnejšiu kauzálnu inferenciu | |
| Program: | Návratová projektová schéma |
| Duration: | 1.7.2025 – 30.6.2026 |
| Project leader: | Mgr. Mezeiová Kristína, PhD. |
| Annotation: | The aim of the project is to explore the use of alternative entropy measures, such as Rényi entropy, Tsallis entropy, and permutation entropy, in the transfer entropy method to enhance the accuracy, robustness, and computational efficiency of causal analysis in complex systems. The project will focus on the software implementation of appropriately modified causal algorithms, their testing on synthetic and real-world data, and the identification of areas where the proposed innovations provide significant advantages. |
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| Štipendiá pre excelentných PhD. študentov a študentky R1 | |
| Program: | Plán obnovy EÚ |
| Duration: | 1.9.2023 – 31.8.2026 |
| Project leader: | Ing. Pajanová Iveta |
| Annotation: | PhD Topic: Application of deep-learning algorithms on automated MRI data processing. Annotation: Automated identification and segmentation of clinical data, obtained primary by MRI, is very desirable. The reason is typically large size of data and therefore enormous time, which radiologist has to invest into the manual segmentation. Availability of powerful hardware open new capabilities to automate this processes and speedup via deep learning techniques using convolutional neural networks (CNN). Therefore, student will learn the fundamental functionality principles of MRI device (theoretically and practically), try manual segmentation of volumetric MRI data, and theoretically and practically learn principles of CNN. Student will design own architecture of CNN for automated segmentation of volumetric data, further train, validate and implement on testing data.The output of this dissertation should be a CNN capable of deployment in clinical practice, in the diagnosis and quantitative analysis of selected tissues (cartilage, ligaments, tendons, menisci, subcutaneous fat, etc.). It is theoretical work, in which programming basics and knowledge of some programming language are necessary. As the programming environment, for design and implementation of CNN, will be used Python with module TensorFlow. |
| cBCI-VR – Collaborative BCI post-stroke neurorehabilitation using a patient-therapist interactive VR environment | |
| Pacient-terapeut kolaboratívna BCI-VR neurorehabilitácia po cievnej mozgovej príhode | |
| Program: | Plán obnovy EÚ |
| Duration: | 1.9.2024 – 31.8.2026 |
| Project leader: | Ing. Mgr. Rosipal Roman, DrSc. |
| Annotation: | A growing body of evidence suggests that integrated brain-computer interface (BCI) technologies and virtual reality (VR) environments provide a flexible platform for a range of neurorehabilitation therapies, including significant motor recovery and cognitive-behavioral therapy following stroke. When a subject is immersed in such an environment, their perceptual level of social interaction is often impaired due to a suboptimal interface quality that lacks the social aspect of human interactions. The project proposes a user-friendly intelligent BCI system with a suitable VR environment in which both patient and therapist interact through their person-specific avatar representations. On the one hand, the patient voluntarily and at his/her own pace controls his/her activity in the environment and interacts with the therapist through a BCI-driven mental imagery process. On the other hand, the therapist\’s unrestricted motor and communication skills allow for full control of the environment. Thus, the VR environment can be flexibly modified by the therapist, allowing for the creation and selection of different occupational therapy scenarios according to the patient\’s recovery needs, mental states, and immediate reactions. |
| TInVR – Trustworthy human–robot and therapist–patient interaction in virtual reality | |
| Dôveryhodná interakcia človek–robot a terapeut–pacient vo virtuálnej realite | |
| Program: | APVV |
| Duration: | 1.7.2022 – 30.6.2026 |
| Project leader: | Ing. Mgr. Rosipal Roman, DrSc. |
| Annotation: | We aim to study specific forms of social interaction using state-of-the-art technology – virtual reality (VR) which is motivated by its known benefits. The project has two main parts, human–robot interaction (HRI) and therapist–patient interaction (TPI). The interactions are enabled using head-mounted displays and controllers allowing the human to act in VR. We propose two research avenues going beyond the state-of-the-art in respective contexts. In HRI, we will develop scenarios allowing the humanoid robot to learn, understand and imitate human motor actions using flexible feedback. Next, we develop scenarios for testing and validating human trust in robot behavior based on multimodal signals. We will also investigate physical interaction with a humanoid robot NICO. In TPI with stroke patients, we develop a series of VR-based occupational therapy procedures for motor and cognitive impairment neurorehabilitation using an active and passive brain-computer interface, and we will validate these procedures. We expect observations from HRI experiments to be exploited in TPI. The proposed project is highly multidisciplinary, combining knowledge and research methods from psychology, social cognition, robotics, machine learning and neuroscience. We expect to identify features and mechanisms leading to trustworthy processes with a human in the loop, as a precondition of success, be it a collaborative task or treatment in VR. |
| EDABSS – EEG data analysis by blind source separation methods | |
| Analýza EEG signálu pomocou metód hľadania skrytých zdrojov | |
| Program: | Plán obnovy EÚ |
| Duration: | 1.9.2024 – 31.8.2026 |
| Project leader: | Mgr. Rošťáková Zuzana, PhD. |
| Annotation: | Blind source separation (BSS) approaches are unsupervised machine learning methods focused on the detection of hidden, directly unobservable (latent) structure of real-world data. They play a crucial role in image processing, medical imaging, and music. The proposed project focuses mainly on human electroencephalogram (EEG), for which BSS is beneficial when detecting the narrowband brain oscillations representing brain processes either in health or disease. Two-dimensional BSS methods like principal or independent component analysis are easily applicable and understandable for a broader medical and neurophysiological community. However, the estimated latent component properties are usually incompatible with the real electrophysiological signal character. Consequently, they miss their neurophysiological interpretation. Tensor decomposition is a complex but more flexible mathematical procedure that allows adapting the model structure and constraints to the solution to mimic real-world signal characteristics. The proposed project focuses on tensor decomposition as a tool for i) EEG preprocessing, artefact detection and removal, ii) EEG latent structure analysis using a nonnegative tensor decomposition with block structure allowing to model various relationships between latent components, and iii) post-decomposition analysis of latent component dynamic properties. Obtaining comprehensive information about EEG latent structure and developing novel, user-friendly algorithms is crucial for better understanding brain processes and new methods for treating neurophysiological diseases and disorders. |
| Research on the correlation dependences of magnetic, structural, and optical properties of aluminate glasses, titanium alloys, and titanium-based nanocolloids, and ion liquids | |
| Výskum korelačných závislostí magnetických, štruktúrnych a optických vlastností hlinitanových skiel, titánových zliatin a nanokoloidov na báze titánu a iónových kvapalín | |
| Program: | VEGA |
| Duration: | 1.1.2025 – 31.12.2028 |
| Project leader: | Mgr. Škrátek Martin, PhD. |
| Annotation: | The project focuses on the development of magnetic measurement methods for selected areas of materialsresearch and biomedicine, for a deeper understanding of the physical and chemical properties associated withchanges in the distribution of electrical charges, and for their utilization in designing revised technologicalprocedures and diagnosing surface properties. First goal of the project is to investigate the influence ofcomposition, precursor powder preparation methods, and the preparation method of aluminateglasses/glass-ceramics on their structure and magnetic properties. The second goal is the investigation of theinfluence of properties and composition of ion liquids on the phase composition, shape, size distribution, andstability of titanium-based nanoparticles and nanostructures. The physicochemical and magnetic properties ofnanocolloids will be studied with attention to the surface properties of biomedical Ti-alloys, especiallynanostructures based on titanium oxide. |
| SQUIDiron – Determination of Iron in blood and tissues of laboratory animals using SQUID magnetometer. | |
| Stanovenie množstva železa v krvi a tkanivách laboratórnych zvierat pomocou SQUID magnetometra | |
| Program: | Plán obnovy EÚ |
| Duration: | 1.9.2024 – 31.8.2026 |
| Project leader: | Mgr. Škrátek Martin, PhD. |
| Annotation: | Iron is an essential chemical element that is part of many metabolic processes. However, the amount of iron in the body must be balanced, as its excess or deficiency can lead to serious health conditions. Iron is found in the body in ferritin, hemoglobin or transferrin proteins. Deoxyhemoglobin, methemoglobin, and myoglobin are known to exhibit paramagnetism, which originates from the Fe2+ Fe3+ ions embedded in their molecules. Ferritin, as an iron storage protein, contains Fe atoms mineralized in the form of oxyhydroxide nanoparticles, whose behavior is superparamagnetic. SQUID magnetometry offers the possibility of detecting and quantifying different forms of iron with high sensitivity and could be more useful than other established methods (colorimetric, spectrophotometric, histochemical or atomic absorption spectrometry) in determining the amount of iron in small samples. |
| Effects of low-frequency and pulsed electromagnetic fields at a cellular level | |
| Účinky nízkofrekvenčných a pulzných elektromagnetických polí na bunkovej úrovni | |
| Program: | VEGA |
| Duration: | 1.1.2025 – 31.12.2028 |
| Project leader: | Mgr. Teplan Michal, PhD. |
| Annotation: | Although there is ongoing interest in the adverse and beneficial effects of electromagnetic fields (EMF), a clearexplanation of EMF\’s influence on living structures is lacking. To investigate low-frequency (LF) magnetic fields(MF), we will enhance our experimental platform to test their possible inhibitory or stimulatory effects based onfrequency and magnetic flux density parameters. As a model organism yeast strain Saccharomyces cerevisiaewill be used. Its response to time-harmonic and pulsed MF will be studied by measuring cell growth curve usingturbidimetry, impedance spectroscopy and microscopy. Moreover, the ion parametric resonance interactionmodel will be verified for biogenic ions and the magnitude of the ambient static geomagnetic field. The importanceof this area of research lies in exploring physical methods for manipulating biological structures, with potentialbenefits for biotechnology and medical treatment. |
| Characteristic function-based goodness-of-fit test for fuzzy data with application to climate analysis | |
| Testy dobrej zhody založené na charakteristickej funkcii pre neurčité údaje s aplikáciou na analýzu klimatických dát | |
| Program: | APVV |
| Duration: | 1.1.2026 – 31.8.2028 |
| Project leader: | Doc. RNDr. Witkovský Viktor, CSc. |
| Annotation: | Modern research faces growing data uncertainty from measurement errors, gaps, and subjective assessments. Traditional statistical methods, assuming precise data, often fail under such conditions. Fuzzy data, which capture vagueness and imprecision, offer a natural framework, yet robust statistical tools for them remain scarce. This interdisciplinary project — combining probability and mathematical statistics, applied mathematics, and measurement science — aims to develop a goodness-of-fit test based on characteristic functions for fuzzy and interval-valued data. This novel methodology addresses both theoretical and applied challenges, with a focus on climate analysis. Objectives include: (1) Developing theoretical and empirical characteristic functions for fuzzy data, defining distance measures, formulating the test, and deriving its statistical properties. (2) Designing and implementing efficient algorithms in R, MATLAB, or Python. (3) Evaluating performance through simulations and benchmarking against existing methods. (4) Applying the method to real climate datasets (e.g., temperature, rainfall) to demonstrate its relevance under uncertainty. The methodology leverages the uniqueness and computational benefits of characteristic functions, extended to fuzzy settings. The project innovatively integrates characteristic functions and fuzzy theory for hypothesis testing, providing a statistically rigorous yet practical approach to imprecise data analysis. Expected outcomes include: a new statistical test, open-source software, simulation and benchmark studies, case studies on climate data, and preparation of a publication in leading journal. This bilateral project brings together expertise in fuzzy theory (University of Montenegro) and measurement science (Institute of Measurement Science of the Slovak Academy of Sciences). |
| Theoretical properties and applications of special families of probability distributions | |
| Teoretické vlastnosti a aplikácie špeciálnych tried rozdelení pravdepodobnosti | |
| Program: | VEGA |
| Duration: | 1.1.2024 – 31.12.2027 |
| Project leader: | Doc. RNDr. Witkovský Viktor, CSc. |
| Annotation: | In the project, problems related to probability distributions and their applications in mathematical modeling will be studied. We will analyze some classes of distributions (distributions generated by partial summations, the Schröter family) and study properties of distributions belonging to these classes. Issues related to calibration regression models will be addressed. New methods for solving multivariate statistical problems will be developed. These methods will be based on the calculation of exact probability distributions using the inverse transformation of the characteristic function of the distribution of the output variable. Entropy, another property of probability distributions, plays an important role in detecting causality in time series. The primary area of application is theuse of the distribution of test statistics in hypothesis testing. The new results obtained during the solution of the project will also be applied to mathematical modeling in metrology, linguistics and actuarial mathematics. |