Find Academic Supervisors

• NMR Spectroscopy
• EPR Spectroscopy
• Solid-state spectroscopy
• +4 more

Dr. Arūnas Maršalka serves as an Associate Professor at the Institute of Chemical Physics, Faculty of Physics, Vilnius University. His research focuses on advanced spectroscopic techniques for studying molecular structures and dynamics, particularly in complex material systems and biological environments. His primary research interests center around NMR (Nuclear Magnetic Resonance) and EPR (Electron Paramagnetic Resonance) spectroscopy applications. Maršalka investigates photochemical processes of sensitizers in oxidant environments, solid-state NMR spectroscopy, hydrogen bonding phenomena, and lyotropic chromonic liquid crystals of biomedical interest. His work spans from fundamental molecular interactions to applied materials science, with particular attention to calcium phosphates used in medical applications and rare-earth-doped materials for optical technologies. Analysis of his recent publications reveals a strong focus on spectroscopic characterization of materials with biomedical relevance. His research demonstrates expertise in combining multiple spectroscopic techniques (NMR, EPR, FT-IR, Raman) with computational methods (DFT) to understand molecular structures and dynamics. A recurring theme across his work is the investigation of hydrogen bonding networks and their role in determining material properties, spanning from organic molecules to complex biominerals. Dr. Maršalka actively supervises student research, having guided multiple bachelor's theses on topics including Vitamin C photochemical reactions using EPR spectroscopy, new generation light technology materials (mixed metal garnets doped with lanthanide ions), and structural properties of calcium phosphates used in medicine. His research has practical applications in photodynamic therapy, LED technology, and biomedical materials development. Outside his primary academic role, Dr. Maršalka serves as Deputy President of the Lithuanian Radio Sports Federation for ARDF affairs, ARDF coordinator of Lithuanian radio amateur society, and is a member of the working group of the International Amateurs Radio Union (IARU), demonstrating a commitment to both scientific and community engagement.

• Vibrational spectroscopy
• Matrix isolation
• Low-temperature chemistry

Rasa Platakytė is an Assistant Professor at the Institute of Chemical Physics, specializing in vibrational spectroscopy and low-temperature matrix isolation techniques. Her research examines molecular interactions, hydrogen bonding dynamics, and photochemical reactions under cryogenic conditions using advanced spectroscopic methods. Research Focus: Her work spans vibrational spectroscopy of isolated molecules, matrix isolation FTIR studies of molecular conformations, hydrogen tunneling phenomena, and photoisomerization mechanisms. Primary methodologies include low-temperature FTIR/Raman spectroscopy combined with computational chemistry approaches. Teaching & Supervision: Since 2018, she has taught optics courses across multiple faculties including Medicine, Physics, and Chemistry. Actively supervises 1-3 bachelor students annually and contributes to physics education through the young physicist school 'Fotonas'. Science Outreach: Organized the 'Cafe Scientifique' lecture series (2018-2022) bringing science to public spaces, and co-organized the international student conference 'Open Readings'.

• Wireless networks
• Gravitation
• Computer networks

Dr. Kęstutis Svirskas is a researcher at the Institute of Applied Electrodynamics and Telecommunications (IAET) at Vilnius University. His work bridges wireless network technologies with theoretical physics, particularly gravitation and particle dynamics. Research Interests include wireless networks, gravitation, and computer networks. He has contributed to electromagnetic compatibility studies and channel modeling for next-generation telecommunications. His article trends reveal interdisciplinary work, combining gravitational theory (e.g., Kerr black holes) with practical wireless network challenges (e.g., LTE performance, DVB-T compatibility, LOS/NLOS channel models). Teaching involves courses like Theory of Relativity, Routing in Local Area Networks, and Computer Communication Technologies at the bachelor's level. He also supervised thesis projects on anechoic chamber calibration and LTE network analysis. Scientific activities include translating Stephen Hawking and Leonard Mlodinov's The Grand Project into Lithuanian, contributing to science education through academic projects.

• Quantum Computing
• Machine Learning
• Medical Image Analysis
• +3 more

Linas Petkevičius serves as an Associate Professor at Vilnius University's Faculty of Mathematics and Informatics, actively teaching courses including Introduction to Quantum Computing across 10 consecutive academic years from 2016/2017 through 2025/2026 as evidenced by institutional schedules. His research demonstrates remarkable interdisciplinary breadth spanning quantum computing algorithm optimization, medical diagnostics through digital pathology analysis, and satellite-based environmental monitoring. He develops machine learning solutions for breast cancer prognosis using Ki67 heterogeneity metrics, creates quantum circuit schemes adapted to hardware constraints, and implements deep learning models for algal bloom detection in Baltic waters using Sentinel-2 data. His work consistently bridges theoretical computer science with practical healthcare and environmental applications. Analysis of his 15 most recent publications (2023-2025) reveals three dominant research thrusts: 1) Quantum computing optimization for NISQ devices, 2) Medical image analysis focusing on spatial tumor microenvironment characterization in breast cancer, and 3) Remote sensing applications using transformer models and few-shot learning for satellite change detection. His publications show increasing specialization in combining deep learning architectures with domain-specific constraints across these fields. Scientific Awards: No scientific awards were mentioned in the provided materials. Advising and Grants: The provided texts contain no information regarding student advisement, research grants, or funded projects.

• Cybersecurity
• Maritime Cyber Resilience
• E-vehicle Routing
• +3 more

Agnė Brilingaitė is an Associate Professor at the Faculty of Mathematics and Informatics, Vilnius University. Her work bridges cybersecurity with transportation systems and mobile services, focusing on practical skill development, risk assessment, and human-centric approaches to security education.

• Machine Learning
• Data Mining
• Fraud Detection
• +2 more

Dalia Breskuvienė is a PhD student and junior researcher at the Cognitive Computing Group of Vilnius University’s Institute of Data Science and Digital Technologies. Her research spans Machine Learning, Data Mining, and Fraud Detection , focusing on optimizing classifier training for highly imbalanced data in financial contexts. Doctoral Studies : Enrolled from 2021 to 2025 under supervisor Prof. Gintautas Dzemyda. Research Focus : Addresses challenges in fraud detection by innovating feature selection, encoding, and training strategies for imbalanced datasets. Publications : Explores autoencoders, clustering techniques, and concept drift in machine learning models. Conferences : Presented her work at annual Computer Science Engineering PhD Student Conferences in Vilnius (2022–2023).

Povilas TreigysView profile

Professor

• Digital Signal Processing
• Machine Learning
• Deep Learning
• +3 more

Professor Povilas Treigys is a Senior Researcher and Group Leader at the Image and Signal Analysis Group within the Institute of Data Science and Digital Technologies at Vilnius University's Faculty of Mathematics and Informatics. With extensive experience in digital signal processing and machine learning applications, he leads research efforts in medical image analysis, speech processing, and maritime traffic modeling. Dr. Treigys earned his Doctor of Science in Computer Science Engineering in 2010 with a dissertation on "Development and application of graphical methods for analyzing ophthalmological and thermovision data." His academic journey has been marked by significant contributions to interdisciplinary research connecting computer science with medical applications. His research primarily focuses on digital signal processing across multiple domains including medical imaging (MRI, eye fundus), audio signals, and maritime traffic data. A key emphasis of his work is the development and application of deep learning methods to solve real-world problems in healthcare diagnostics, retail automation, and transportation safety. His recent work demonstrates a strong trend toward explainable AI in medical applications and sophisticated time series analysis for prediction tasks. Professor Treigys serves in numerous leadership roles including as a EuroHPC JU Board Member representing Lithuania, VU MIF representative on the Lithuanian Quantum Technology Association board, and as a delegate to multiple professional committees. He is an active reviewer for several prestigious journals including Computer Science, Nonlinear Analysis, Baltic Journal of Modern Computing, MDPI Sensors, and MDPI Electronics. His laboratory focuses on bridging theoretical machine learning advancements with practical applications, particularly in medical diagnostics where his team has made significant contributions to prostate cancer detection, arrhythmia classification, and ophthalmological image analysis. The group maintains strong international collaborations and regularly presents findings at major conferences in computer vision, medical imaging, and artificial intelligence.

• Analytic Number Theory
• Riemann Zeta Function
• Dirichlet L-functions
• +5 more

Professor Igor Belov is a Senior Researcher and Professor at Vilnius University's Institute of Data Science and Digital Technologies, specializing in analytic number theory, information security, and mathematical modeling. His research spans theoretical mathematics with practical applications in finance and computer science, particularly focusing on zeta functions, prime number theory, and stable distribution models. Education: Doctor of Physical Sciences (Mathematics) from Vilnius University and Vilnius Gediminas Technical University (2004) Master's degree in Statistics from Vilnius University (1999) Bachelor's degree in Mathematics Applications from Vilnius University (1997) Professor Belov's research interests center on analytic number theory with emphasis on Riemann zeta function and Dirichlet L-functions, combinatorial analysis, information security, and mathematical modeling of financial data using stable distributions. His recent work explores fractal structures related to zeta functions, efficient algorithms for zeta function calculations, and applications of machine learning in financial document analysis and securities price forecasting. His publication record demonstrates a strong trajectory from pure mathematical research toward interdisciplinary applications. While maintaining a robust foundation in analytic number theory, his recent work increasingly bridges theoretical mathematics with practical computing applications, particularly in financial modeling and information security. This evolution reflects a strategic expansion of his research impact across multiple domains. Scientific Awards: 1st place at the Vilnius Young Mathematicians' Olympiad (1990) Honorable mention at the Lithuanian Young Mathematicians Olympiad (1991) Letter of Commendation at the Lithuanian Young Mathematicians Olympiad (1992) Professor Belov actively supervises doctoral research and has served on numerous dissertation defense committees. He currently mentors four doctoral students working on zeta function algorithms, financial forecasting, document recognition, and blockchain acceleration. His research has been supported by multiple grants including the LMT project P-SV-23-9 on Mandelbrot bulbs visualization associated with the Riemann zeta function. He has also participated in international research collaborations at CINECA supercomputing center and Karlsruhe Institute of Technology. As a member of the Smart Technologies Research Group, Professor Belov contributes to Vilnius University's leadership in mathematical research and its applications, particularly in the areas of zeta function analysis and computational finance.

• Stochastic Programming
• Mathematical Modeling
• Financial Mathematics
• +7 more

Prof. habil. dr. Leonidas Sakalauskas is an Affiliated Scientist at the Smart Technologies Research Group within the Institute of Data Science and Digital Technologies at Vilnius University. His extensive research career spans mathematical modeling, stochastic programming, and statistical analysis with significant contributions across multiple disciplines. He maintains an active research profile with recent publications extending into 2025. Professor Sakalauskas' research focuses on stochastic programming, mathematical modeling, financial mathematics, statistical analysis, optimization, and queueing theory. His work demonstrates a consistent pattern of interdisciplinary research, bridging theoretical mathematics with practical applications in finance, social sciences, and computer science. He has developed innovative approaches to agent-based modeling, fractal analysis, and Monte Carlo methods, contributing significantly to both theoretical frameworks and practical implementations. His recent publications reveal a continuing evolution of research interests, with increasing emphasis on data science applications, computational social science, and advanced statistical modeling techniques. The articles demonstrate sophisticated methodological approaches to complex problems across diverse domains including financial modeling, social cohesion analysis, and network performance optimization. Throughout his career, Professor Sakalauskas has maintained a strong publication record in high-impact journals and conference proceedings, reflecting his ongoing engagement with the international research community. His work shows consistent methodological rigor combined with practical relevance across multiple application domains. Professor Sakalauskas has collaborated extensively with researchers across Lithuania and internationally, demonstrating strong teamwork and interdisciplinary engagement. His research has practical applications in financial modeling, social science analysis, and computational systems optimization, contributing to both theoretical advances and real-world implementations.

Laura RingienėView profile

Researcher

• Educational Data Analysis
• Statistical Modeling
• Multilevel Regression
• +4 more

Laura Ringienė is a Researcher and Information Technology Administrator at Vilnius University's Institute of Data Science and Digital Technologies, where she works in the Interdisciplinary Statistical Research Group. She holds a PhD in Computer Science Engineering obtained in 2014 from Vilnius University's Institute of Mathematics and Informatics. Her professional activities span research, teaching, and technical administration within the academic environment. Dr. Ringienė earned her educational credentials at Vilnius Pedagogical University, completing her Bachelor's degree in Informatics in 2006 and Master's degree in Informatics in 2008, both from the Faculty of Mathematics and Informatics. Her doctoral dissertation, Hybrid Neural Network for Multidimensional Data Visualization , was defended in 2014 and falls under Technological Sciences, Computer Science Engineering. Her research focuses on statistical analysis of educational data, with particular expertise in multilevel regression, structural equation modeling, and analysis of international large-scale assessment data (PISA, TIMSS, PIRLS). She has developed the R program package EFECTAS specifically designed for analyzing international education research data. Her work examines educational equity, reading achievement gaps across EU countries, socioeconomic factors affecting student performance, and the impact of preschool education on later academic outcomes. Analysis of her publication record from 2020-2025 reveals a strong concentration on educational data science, with recurring themes of statistical modeling of international assessment data, educational equity analysis, and application of advanced statistical techniques to understand educational systems across Europe. Her work frequently employs PISA, TIMSS, and PIRLS datasets to examine cross-national educational patterns and policy implications. Dr. Ringienė has been actively involved in the EFECTAS project (2018-2022), which was financed by the European Social Fund under a grant agreement with the Research Council of Lithuania. This project focused on analyzing the efficiency and productivity of education systems in EU countries using secondary large-scale data. She teaches undergraduate courses at Vilnius University, including Big Data Analytics and Business Process Robotization since 2019. Her professional development includes extensive training in Robotic Process Automation (UIPath), Structural Equation Modeling, Multilevel Linear Modeling, and various Big Data technologies. She is part of the Interdisciplinary Statistical Research Group, which focuses on applying advanced statistical methods to solve complex problems in education and other domains.

• Composite Materials
• Nanomaterials
• Smart Materials
• +3 more

Gediminas Monastyreckis is a Researcher at Kaunas University of Technology (KTU) specializing in advanced composite materials for aerospace and renewable energy applications. His work focuses on nanomaterial-enhanced polymer systems with multifunctional capabilities. Research interests include: Self-sensing composites for structural health monitoring using carbon-based and MXene nanomaterials Adhesion enhancement through star-like copolymer additives in basalt/epoxy systems De-icing technologies for wind turbine blades using electrothermal nanocoatings Sustainable composites with bio-based matrices and natural fiber reinforcements Localized curing methods for aviation composite bonding Analysis of his 15 most recent publications (2022-2025) reveals a strong trend toward multifunctional composites integrating 2D nanomaterials. Key themes include real-time damage mapping through electrical conductivity changes, sustainable material development using bio-resins, and scalable manufacturing of nanocoatings for extreme environments. His work bridges computational modeling with experimental validation, particularly in hydrothermal aging and impact resistance.

Achilleas AchilleosView profile

Lecturer

• Pervasive Computing
• Mobile Computing
• Adaptive Web Engineering
• +7 more

Achilleas Achilleos serves as a Lecturer at Frederick University's School of Engineering, Department of Electrical and Computer Engineering and Informatics, and co-directs the Mobile Devices Laboratory (MDL) within the Frederick Research Center. His academic leadership spans software architecture design for adaptive systems and pervasive computing environments. Ph.D. in Computer Science, University of Essex (EPSRC/BT co-funded) M.Sc. in Computer and Information Networks B.Sc. in Computer Engineering His research centers on engineering methodologies for context-aware systems, with emphasis on IoT integration and smart city applications. He develops model-driven frameworks bridging service-oriented architectures and cloud computing infrastructures to address real-time adaptability challenges in mobile environments. As MDL Lab co-director, he manages a 5-member research team executing 10 active and 3 completed projects including EUROSTARS AURA-CARE, Erasmus+ OLMEdu (as coordinator), and EU H2020 initiatives. His work demonstrates strong industry-academia collaboration through British Telecom partnerships and national innovation projects like SportsTraveler76.

• Mathematics Education
• Digital Transformation in Education
• Communication Skills in Mentoring
• +4 more

Associate Professor Vaida Bartkutė-Norkūnienė of Utena College is an active researcher in mathematics education, digital transformation, and mentoring communication. Her work bridges technical disciplines with practical applications in education and sustainability. Her primary research interests include: Mathematics education methodologies and computerized learning systems Digital CO2 footprint analysis for websites and e-commerce Cross-national mentoring communication frameworks Labor market policy efficiency in EU contexts Digital innovation adoption in tourism sectors Recent publications demonstrate a clear trajectory toward sustainable digital practices, with significant focus on quantifying environmental impacts of web technologies while advancing educational models through AI integration. Her cross-cultural mentoring studies reveal critical communication patterns between Lithuanian and Latvian academic systems. Dr. Bartkutė-Norkūnienė manages multiple high-impact projects including the National Education Agency's 'Digital Transformation of Education (EdTech)', NORDPLUS 'Network Water Quality and Food Safety', and Erasmus+ 'DICCMEM' communication competence initiatives. She secured Ministry of Education funding for youth programs 'Start a career with an idea' (2021) and 'Code - Keys to Success' (2020). She actively contributes to academic governance as editorial board member of 'Įžvalgos' journal, program committee member for ISC SAI 2022, and Scientific Activities Subgroup member developing ethical AI guidelines for science. Her professional affiliations include the Lithuanian College Mathematics Teachers Association, National Distance Learning Association, and European Working Group on Stochastic Programming.

Pierre SemalisView profile

Professor

• Operations Management
• Logistics
• Supply Chain Management
• +3 more

Prof. Pierre Semalis is a Professor at the Leuven School of Management of the Catholic University of Leuven , specializing in management and operations management. He co-founded the Supply Chain Management Center of Excellence and contributed to the development of the Baltic Management Institute (BMI). He has held leadership roles including Dean (1999–2005), Director for International Development (2005–2008), and Executive Director (2008–2009). As a visiting professor, he has taught globally in cities like Paris, Krakow, Shanghai, and Vilnius. He actively participates in CEMS (Global Alliance in Management Education), serving as its Vice President (2002–2009) and Academic Director of its annual research seminar. Education: Bachelor’s in Applied Mathematics, Catholic University of Leuven PhD in Applied Sciences, Catholic University of Leuven (1992) Research Focus: Semalis is a leading authority in supply chain management, logistics, and operations management. His work emphasizes international collaboration, reflected in projects like the triennial Supply Chain Research Seminar with Antwerp, Rotterdam, and Eindhoven universities. Awards: IBM Belgium 1993 Prize Belgian National Research Foundation’s Best Dissertation in Computer Science (1993) International Contributions: He pioneered VMU’s double-degree program with Leuven (2011), strengthening Lithuania’s academic ties. Through BMI and CEMS, he bridges European universities with multinational firms, enhancing management education globally. His leadership in strategic alliances and academic networks underscores his commitment to institutional excellence. Labs/Teams: Organizes the biennial Supply Chain Research Seminar and directs CEMS’ logistics initiatives. Active in BMI’s Executive MBA programs since 1999.

Tadas ŽižiūnasView profile

Researcher

• Cultural Heritage Preservation
• 3D Technologies
• Artificial Intelligence Applications
• +3 more

Tadas Žižiūnas is a researcher at the Faculty of Communication , Vilnius University , specializing in the intersection of 3D technologies , artificial intelligence , and cultural heritage preservation . His work focuses on developing automated systems for monitoring urban heritage, applying advanced digital methods to historical artifact analysis, and integrating spectroscopy with 3D modeling in archaeological contexts. Academic Qualification: PhD (2019) in cultural heritage research, Vilnius University Key research areas include digital urban heritage practices , AI-driven preservation tools , and 3D technology applications in archaeology . His publications demonstrate a consistent focus on technological innovation in heritage management, with projects funded by the European Regional Development Fund (2018–2022). His recent work explores democratization of heritage conservation through 3D scanning and AI, while earlier contributions examined spectroscopy for historical document analysis and augmented reality for preserving genius loci in urban settings. Notable projects include the Automated Heritage Monitoring of Urbanised Areas initiative, which combines AI with 3D digitization to assess risks to cultural assets.