| Topic title |
Possible scientific supervisors |
Source of funding |
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Ultrasonic Guided Wave Structural Integrity Assessment of Thermally Induced Healing Thermoplastic Composite Structures
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prof. dr. Elena Jasiūnienė |
state-funded |
Research Topic Summary.
Nowadays thermoplastic composite structures, among other advantages, are gaining popularity due to their recyclability properties. Particularly attractive is the ability of thermoplastic composites to retain their properties after being melted and consolidated. The idea is that this ability could be used for self-healing. However, it is necessary to verify the quality of self-healing, and for that ultrasonic guided waves could be used. Ultrasonic guided waves have proved to be sensitive to the changes in the material properties and are able not only to detect different defects, providing indication of damage, but also to assess their size and location. In addition, ultrasonic guided waves can travel long distances, thus allowing the inspection of large structures.
The objective is to develop a new ultrasonic guided waves method to monitor and evaluate the structural integrity of thermoplastic composite structures with thermally induced healing capabilities.
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| Research on a multifunctional hybrid chip for efficient energy management |
prof. dr. Algimantas Valinevičius |
state-funded |
| Problems and development of non-invasive technologies for physiological monitoring of human brain and for neuroprotection of brain functions. |
prof. dr. Arminas Ragauskas |
state-funded |
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Application of artificial intelligence methods for analysis of informative regions within ultrasonic NDT and medical diagnostic images
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prof. dr. Renaldas Raišutis |
state-funded |
Research Topic Summary.
The scientific problem includes the informative analysis of ultrasound signals and diagnostic images and the quantitative interpretation of the results in order to detect internal defects and pathologies. The aim is to develop and investigate the methods of analysis of informative areas in ultrasound non-destructive testing and medical diagnostic images, providing opportunities for quantitative parameter measurement and automated classification of these areas (internal defects and various pathologies), using artificial intelligence methods. The research will use advanced research infrastructure with global relevance.
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| Research of energy harvesting from environment for electronic devices |
prof. dr. Dangirutis Navikas |
state-funded |
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Efficient signal excitation and processing technologies for ultrasonic measurements and imaging
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prof. dr. Linas Svilainis |
state-funded |
Research Topic Summary.
Measurement and imaging resolution demand for reliable signals separation, but limited bandwidth is causing the signals to overlap. Research is aimed to develop the efficient signal excitation and processing techniques for ultrasonic imaging and measurements. Reliable time of flight and reflection amplitude estimation, imaging resolution and contrast are improved thanks to binary excitation spread spectrum signals application. Overlapping reflections are resolved either by spectroscopic or iterative deconvolution techniques. Correlation sidelobes, signal bandwidth can be optimized/corrected thanks to innovative excitation signals. Excitation is not limited to conventional acoustic sources, but also photoacoustics can be used. Laser ultrasound excitation can use spread spectrum signals which in turn can be adapted to spectral/correlation properties requirements. Reference signals can be made adaptable in order to increase the deconvolution efficiency. New signal quality is obtained thanks to efficient excitation and processing, which in turn enhances the possibilities for imaging and measurements.
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| Low-Power Energy Harvesting Architectures for IoT Devices |
prof. dr. Vytautas Markevičius |
state-funded |
| Optimization of cell-free mMIMO technology network performance and electromagnetic pollution in urban environments |
prof. dr. Darius Andriukaitis |
state-funded |
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Research Methods for Anomaly and Fault Detection in Power Systems
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prof. dr. Žilvinas Nakutis |
state-funded |
Research Topic Summary.
The aim of the research is to develop methods, algorithms and equipment for the detection of anomalies and faults in energy systems and infrastructure (power distribution grid, battery energy storage, renewable energy systems, measuring equipment, communication infrastructure) and to characterize them in terms of accuracy, delay and energy efficiency. Monitoring (physical measurements) of complex systems consisting of many structural components is restricted to a limited number of locations due to cost and physical limitations. Therefore, there exist challenges in creating equivalent system models that can be adapted to a specific system using data-driven methods. The created models can be used to detect anomalies/defects by comparing the system parameters predicted by these models with the real measurement results. To design models, it is planned to combine analytical physical systems models and models generated by machine learning.
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Development and scientific development of a collaborative robot system research
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prof. dr. Renaldas Urniežius |
state-funded |
Research Topic Summary.
Are you ready to pursue a PhD in collaborative robotics? Join our team to push the boundaries of deep-tech in cobots, building on our previous designs showcased here: https://youtu.be/DvgsmHiadhQ
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Advanced Ultrasonic Monitoring methods for Long-Term Safety of Nuclear Power Plants
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vyresn. m. d. dr. Vykintas Samaitis |
state-funded |
Research Topic Summary.
This PhD project focuses on improving the safety and longevity of nuclear power plants (NPPs) by developing cutting-edge Structural Health Monitoring (SHM) and ultrasonic inspection methods. Building on successful techniques from aerospace and civil engineering, this research adapts them to the unique demands of NPPs.
Key innovations include real-time defect detection in metallic pipes, advanced signal processing, and AI-powered solutions. The project will also design digital twins to simulate operational conditions and validate methods on actual NPP components and test facilities across Europe.
Supported by the Horizon Europe Euratom program, the PhD candidate will collaborate with leading European research organizations, contributing to safer and more efficient NPP operations.
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Non-invasive methods for monitoring cardio-renal function in heart failure patients
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doc. dr. Andrius Rapalis |
state-funded |
Research Topic Summary.
Heart failure (HF) is a complex disease with high one-year mortality and hospitalization rates. Up to 50% of all deaths in HF patients are due to sudden cardiac death, commonly caused by arrhythmias. While the arrhythmogenesis of HF is multifactorial, appropriate management of two classic complications of HF (fluid congestion and electrolyte imbalance) can reduce adverse outcomes. Symptomatic and severe congestion accounts for about 90% of hospitalizations in HF. Despite best practice guidelines, re-hospitalization for congestion within 6 months occurs in almost 50% of cases, and the mortality risk increases with each case. Electrolyte imbalances cause heart problems that can lead to arrhythmias and require regular monitoring. The gradual electrolyte fluctuations that occur with worsening HF are asymptomatic and can only be detected by a blood test. Blood tests are difficult to perform daily and cannot be done at home, preventing rapid correction of electrolyte imbalance. Fluid congestion and electrolyte imbalance result from impaired cardio-renal function, as there is a synergistic relationship between them, and dysfunction of one organ affects the other. Although the gold standard markers of cardio-renal function are biological, some physiological parameters may be indirect surrogates for assessing impaired cardio-renal dysfunction. The work aims to develop non-invasive methods for HF status monitoring using physiological markers of cardio-renal function. Non-invasive cardio-renal function monitoring will enable further research to improve clinical assessment of HF and other diseases with impaired cardiac and renal function. The work results may positively influence the development of new consumer healthcare devices or systems with integrated cardio-renal function monitoring.
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