Nacionaliniai projektai EN

Title of the project Quantum Algorithms for Advanced Logistics: Optimization of Transport Routing, Pickup-and-Delivery, and Electric Vehicle Infrastructure

Program Information technology for the development of science and the knowledge society

Project number Nr. S-ITP-25-5

Project implementation period 2025-09-01 – 2027-08-31

Head of Project prof. dr. Remigijus Paulavičius

Aim of the project – This project aims to develop and validate quantum-based algorithms for addressing critical logistics challenges—specifically Vehicle RoutingProblems (VRPs), Pickup and Delivery Problems (PDPs), and Electric Vehicle (EV) charging station optimization. By leveraging quantum computing’s capability to handle combinatorial complexities more efficiently than traditional HPC methods, the initiative seeks to enhance last-mile distribution, minimize environmental impact, and streamline the deployment of electric vehicles. These innovations will lead to reduced carbon emissions, lower operational costs, and improved transport efficiency, aligning with both national and global sustainability goals. Algorithms will be tested and benchmarked on real-world datasets, employing commercial quantum hardware (e.g., D-Wave, IBMQuantum) and high-performance simulators (Qiskit Aer, Cirq). This integrated approach not only strengthens Lithuania’s and the broader EU’s engagement in quantum research, but also advances workforce development through targeted training, hands-on workshops, and close industry collaboration. By pushing the boundaries of quantum optimization in logistical applications, the project aims to foster sustainable urban mobility and set the stage for future large-scale quantum-driven innovations that benefit academia, industry, and society alike.

The project is being carried out by a group of highly competent scientists. – prof. dr. Remigijus Paulavičius, dr. Ernestas Filatovas, dr. Dzmitry Padkapayeu, dr. Marco Marcozzi.

Young scientists and students are also participating in the project and developing their skills. - Sasan Ansarian Najafabadi, Glauco Endrigo Moura de Lima ir kt.

Source of funding - Funding was provided by the Lithuanian Science Council (LMTLT), contract No. S-ITP-25-5.

Title of the project Denoising Diffusion Probabilistic Models for Enhanced ECG Signal Noise Reduction in arrhythmia Classification, and AFIB Detection

Program Information technology for the development of science and the knowledge society

Project number Nr. S-ITP-25-9

Project implementation period 2025-10-01 – 2027-09-30

Head of Project dr. Jolita Bernatavičienė

Aim of the project – Cardiovascular diseases are a major cause of mortality worldwide, and accurate ECG analysis is important for early detection and pathological changes identification. However, real-world ECG signals are often corrupted by noise, such as baseline wander and electromyographic artifacts, reducing the reliability of arrhythmia and AFIB detection. This project aims to investigate and develop a novel approach for ECG signal noise reduction using Denoising Diffusion Probabilistic Models (DDPMs). By leveraging the strengths of DDPMs in modeling complex data distributions and generating high-quality samples, we aim to enhance the accuracy and reliability of arrhythmia classification and Atrial Fibrillation (AFIB) detection, particularly in noisy real-world ECG signals acquired from wearable devices like Zive'sECG monitor. The project will address the limitations of existing noise reduction techniques and contribute to advancements in personalized cardiac monitoring and AI-driven telemedicine. By reducing noise distortions, this project will significantly improve automated arrhythmia and AFIB detection, enabling earlier diagnoses and better patient outcomes. Additionally, synthetic ECG data generation using DDPMs will address class imbalances in medical datasets, enhancing AI model performance and reliability. This interdisciplinary collaboration between Vilnius University and Zive IAS leverages expertise in machine learning, biomedical signal processing, and real-world ECG monitoring. The project’s results will support telemedicine, wearable health technologies, and AI-driven cardiology, contributing to more accessible and reliable healthcare solutions.

The project is being carried out by a group of highly competent scientists. – dr. Jolita Bernatavičienė, dr. Jurgita Markevičiūtė, dr. Povilas Treigys, dr. Kęstutis Juškevičius.

Young scientists and students are also participating in the project and developing their skills.

Source of funding - Funding was provided by the Lithuanian Science Council (LMTLT), contract No. S-ITP-25-9.