Faculty of Mathematics and Informatics

Faculty of Mathematics and Informatics

Sukurta: 15 May 2022

mifNaugarduko 24, LT-03225 Vilnius
Didlaukio 47, LT-08303 Vilnius
Akademijos 4, LT-08412 Vilnius
Tel. 219 3050
E-mail: http://www.mif.vu.lt

Dean – Prof. Dr Paulius Drungilas

STAFF

153 teachers (incl. 100 holding research degree), 61 research fellows (incl. 52 holding research degree), 76 doctoral students.

DEPARTMENTS OF THE FACULTY
Institute of Data Science and Digital Technologies
Institute of Computer Science
Institute of Mathematics
Institute of Applied Mathematics

RESEARCH AREAS

Integrated Development of Mathematics, Informatics and Information Technologies for the Knowledge Society Advanced Products and Services
Informatics
Informatics Engineering: Signal Analysis, Machine Learning, Deep Neural Networks
Blockchain Technologies
Fundamental Mathematics: Number Theory, Probability Theory and Stochastic Analysis, Risk Theory, Theory of Differential Equations, Functional Analysis
Applied Mathematics: Methods of Mathematical Statistics, Mathematical Modelling, Finance and Isurance Mathematics, Modern Elementary Mathematics and Didactics, Econometrics, Time Series Analysis

DOCTORAL DISSERTATIONS MAINTAINED IN 2021

A. Jurgelevičius. Hybrid distributed computing sharing platform.
M. Jusis. Method of data synchronization of autonomous port handling processes.
M. Morkūnas. Development of tumor microenvironment-oriented digital pathology methods for whole slide image segmentation and classification.
J. Venskus. Semi-supervised and unsupervised machine learning methods for sea traffic anomaly detection.
A. Daranda. Machine learning-based prediction of the behavior of marine traffic participants and discovering non-standard marine traffic situations.
L. Stripinis. Improvement, development and implementation of derivative-free global optimization algorithms.
R. Astrauskas. Computer modelling of reaction-diffusion processes in scanning electrochemical microscopy and in cell spheroids.
A. Nečiporenko. Mathematical modeling of bioreactor control.
G. Bagdonas. A class of bivariate copula mappings.
R. Gylys. Application of Lee-Carter mortality projection model and its modifications in modelling of solvency capital of insurance company.
G. Lileika. Weak approximations of CKLS model by discrete random variables.
G. Vadeikis. Weighted universality theorems for the Riemann and Hurwitz zeta-functions.
A. Vaiginytė. Approximation of the analytic functions by shifts of zeta-functions of certain cusp forms.

MAIN CONFERENCES ORGANIZED IN 2021

12th conference Data Analysis Methods for Software Systems, 2–4 December 2021, Druskininkai, Lithuania.

14th international conference on Informatics Education Research, 3–5 November 2021, Utrecht, The Netherlands.

Conference on Probability and Number Theory dedicated to 60th anniversary of the Department of Probability Theory and Number Theory of Vilnius University. 14–19 September 2021. Palanga, Lithuania.

8th European Congress of Mathematics, Minisymposia Multiscale Modeling and Methods: Application in Engineering, Biology and Medicine, 20–26 June 2021 (online).

International workshop Mathematical Modeling in Hemodynamics, 8 December 2021, Saint-Etienne and online.

MAIN SCIENTIFIC ACHIEVEMENTS IN 2021

Monograph Mathematical modeling of biosensors. 2nd edition, Springer. 2021, authored by R. Baronas, F. Ivanauskas, and J. Kulys.

Monograph Bayesian and high-dimensional global optimization. Springer. 2021, authored by A. Zhigljavsky and A. Žilinskas.

The asymptotic lower and upper bounds are obtained for the tails of higher-order moments of sums with heavy-tailed increments.
 

INSTITUTE OF DATA SCIENCE AND DIGITAL TECHNOLOGIES

mii

 

Akademijos 4, LT-08412 Vilnius
Tel. 210 9300
E-mail:
http://www.mii.lt
Director – Prof. Dr Habil. Gintautas Dzemyda

 

 

GROUPS OF THE INSTITUTE

Blockchain Technologies Group
Cognitive Computing Group
Cyber-Social Systems Engineering Group
Education Systems Group
Global Optimization Group
Image and Signal Analysis Group
Intelligent Technologies Research Group
Statistics and Probability Group
Artificial Intelligence Laboratory

RESEARCH AREAS

Integrated development of mathematics, informatics and information technologies for the knowledge society advanced products and services


BLOCKCHAIN TECHNOLOGIES GROUP

Akademijos 4, LT-08663 Vilnius
Tel. 219 3299
E-mail:
Head – Dr Remigijus Paulavičius

STAFF

Research professor: Prof. Dr R. Paulavičius.
Senior researchers: Dr E. Filatovas, Dr V. Medvedev.
Researcher: Dr L. Stripinis.
Lecturer: Dr A. Igumenov.
Doctoral students: S. Grigaitis, J. Arsenjeva, R. Bieliauskas, A. Budžys, M. Hassan.

RESEARCH INTERESTS

Blockchain technologies
Global optimization
Optimization software
Multi-objective optimization
High-performance computing
Artificial intelligence
Image processing
Big Data

RESEARCH PROJECTS CARRIED OUT IN 2021

Projects Supported by University Budget

Research and Development of Public, Private and Consortium Type Blockchain Systems. Prof. Dr R. Paulavičius. 2018–2022.

Investigation of the most popular and recent consensus algorithms, such as Proof of Work (PoW), Proof of Property (PoS), Proof of Authorship (PoA), Proof of Importance (PoI), Delegated Byzantium Fault Tolerance (dBFT), etc. Survey of on-chain and off-chain blockchain technology solutions to identify those with the most significant potential to enhance the performance and functionality of currently developed platforms/applications. Experimental analysis of the most popular and emerging algebraic modeling languages, considering a range of relevant comparison criteria. Investigation of data fusion approaches and solutions to identify those integrated into decision-making. Exploration of the potential of machine learning techniques to prevent intrusions in computer networks.

Main publications:

Paulavičius, R., Grigaitis, S., Filatovas, E. A Systematic Review and Empirical Analysis of Blockchain Simulators. IEEE Access. 2021, 9: 38010–38028. DOI: 10.1109/ACCESS.2021.3063324.

Stripinis, L., Žilinskas, J., Casado, L. G., Paulavičius, R. On MATLAB experience in accelerating DIRECT-GLce algorithm for constrained global optimization through dynamic data structures and parallelization. Applied Mathematics and Computation. 2021. DOI: 10.1016/j.amc.2020.125596.

Orts, F., Cucura, A. C., Ortega, G., Filatovas, E., Garzón, E. M. Optimal fault-tolerant quantum comparators for image binarization. The Journal of Supercomputing. 2021, 77(8): 8433–8444. DOI: 10.1007/s11227-020-03576-5.

Stripinis, L., Paulavičius, R. A. new DIRECT-GLh algorithm for global optimization with hidden constraints. Optimization Letters. 2021, 15: 1865–1884. DOI: 10.1007/s11590-021-01726-z.

National Research Projects

Research Council of Lithuania. Resolving Research Reproducibility Problems in Artificial Intelligence using Blockchain Technologies (No. P-MIP-21-196). Dr E. Filatovas. 2021–2024.

Today, most real-world challenging decision problems (image analysis, voice and face recognition, planning, scheduling, routing, etc.) are solved by employing various Artificial Intelligence techniques. However, Artificial Intelligence research domains (as well as other research fields) face with Reproducibility Crisis. Researchers have difficulties reproducing many key results due to the disconnection between publications and used codes, underlying data, parameter settings, etc. as they lack critical details. Solutions that improve code accessibility, data provenance tracking, research transparency, auditing of obtained results and trust in Artificial Intelligence domains can significantly accelerate algorithm and model development, validation, and transition into real-world applications. Thanks to the features provided by Blockchain Technology, great progress in resolving Reproducibility Crisis and full reproducibility can be achieved.
In this context, the project's main objective is to contribute resolving research reproducibility problems in the Artificial Intelligence field and enhance the research cycle by developing a conceptual model of a blockchain-based decentralized platform, which would be efficient, scalable, interoperable, and adaptable in various Artificial Intelligence research domains.

Main publication:

Gudžius, P., Kurasova, O., Darulis, V., Filatovas, E. Deep learning based object recognition in multispectral satellite imagery for realtime applications. Machine Vision and Applications. 2021, 32(4): 1–14. DOI: 10.1007/s00138-021-01209-2.

International Research Projects

High Performance Computing to Optimize Intensity Modulated Radiotherapy Schedules (UAL18-TIC-A020-B). Andalusian Board, Spain. Dr E. Filatovas – Lithuania’s representative. October 2019–October 2021.

Main publication:

Moreno, J. J., Miroforidis, J., Filatovas, E., Kaliszewski, I., Martín, G., Gracia, E. Parallel radiation dose computations with GENOCOP III on GPUs. The Journal of Supercomputing. 2021, 77(1): 66–76. DOI: 10.1007/s11227-020-03254-6.

MAIN R&D&I (RESEARCH, DEVELOPMENT AND INNOVATION) PARTNERS

Imperial College London (UK)
Universidad de Almería (Spain)
Systems Research Institute, Polish Academy of Sciences (Poland)
Kharkiv National University of Radio Electronics, Computer Science Faculty (Ukraine)
Octeract Optimisation Intelligence (UK)

OTHER RESEARCH ACTIVITIES

Dr R. Paulavičius –

  • member of the Young Academy of the Lithuanian Academy of Sciences;
  • member of the Artificial Intelligence and Digital Transformation working group of the Arqus University Alliance;
  • topic editor of the journal Mathematics;
  • affiliate member of European Network of Excellence on High Performance and Embedded Architecture and Compilation (HiPEAC), www.hipeac.net;
  • member of the Lithuanian Computer Society (LIKS);
  • member of Lithuanian Mathematical Society.

Dr E. Filatovas –

  • member of International Society on Multiple Criteria Decision Making (MCDM);
  • member of the Lithuanian Computer Society (LIKS);
  • member of Program/Scientific Committees.

Dr V. Medvedev –

  • member of Lithuanian Computer Society, http://www.liks.lt/;
  • member of Lithuanian Mathematical Society, http://www.mif.vu.lt/lmd/;
  • member of Program/Scientific Committees:
    ○ program committee member of the International Workshop on Secure Mobile Cloud Computing (IWoSeMC-20, IWoSeMC-2022), http://iwosemc.eu/;
    ○ organizing committee member of the Conference on Data Analysis Methods for Software Systems (DAMSS), Druskininkai, Lithuania, https://www.mii.lt/damss.

Dr L. Stripinis –

  • project researcher in the National Research Project (P-MIP-21-196).

Dr A. Igumenov –

  • member of Lithuanian Computer Society, http://www.liks.lt/;
  • project researcher, EU co-funded project No. 01.1.1-CPVA-V-701-15-0001 Development of Vilnius STEAM Center activity Preparation of the Methodological Part of STEAM Center activities: Development of Laboratory Descriptors and Integrated Methodologies for Mobile Technology and Visual Programming Laboratory, http://steamlt.lt/.


COGNITIVE COMPUTING GROUP

Akademijos 4, LT-08663 Vilnius
Tel. 210 9300
E-mail:
Head – Prof. Dr Habil. Gintautas Dzemyda

STAFF

Research professors: Prof. Dr Habil. G. Dzemyda, Prof. Dr Jakaitienė, Prof. Dr. K. Dučinskas, Prof. Dr O. Kurasova.
Research professors of projects: Dr R. Dukynaitė, Dr G. Dzemydaitė, Dr G. A. Melnik-Leroy, Dr S. Raižienė, Prof. Dr Habil. R. Želvys.
Researchers: Dr R. Karbauskaitė, Dr G. A. Melnik-Leroy, Dr A. Usovaitė.
Research assistants: Dr M. Sabaliauskas, Dr D. Stumbrienė, V. Tiešis, J. Vaitekaitis.
Teaching assistants: Dr M. Sabaliauskas, Dr D. Stumbrienė.
Research assistants: Dr I. Katin, Dr L. Ringienė, Ž. Vaišnoras.
Other staff: R. Gipiškis, L. Mikalauskienė, V. Palkevič, Dr L. Ringienė, Dr M. Sabaliauskas, A. Šubonienė, V. Tiešis.
Doctoral students: D. Breskuvienė, V. Bulavas, R. Gipiškis, P. Gudžius, M. Karaliutė, G. Krasauskas, N. Kondrat, M. Motiejauskas, I. Pocė, R. Puronaitė, Ž. Vaišnoras, R. Vaišnorė.

RESEARCH INTERESTS

Artificial neural networks
Big data
Bioinformatics
Data mining
Deep learning
Global optimization methods
Multi-objective optimization
Image analysis, feature detection, image reconstruction, medical image processing
Internet data mining
Fractal dimensionality
Local optimization methods
Machine learning
Medical data analysis and decision support
Multiple criteria decision support
Operations research
Optimal control applications
Parallel computing
Simulation models in epidemiology, education, economics, and energy with uncertainty
Statistical simulation
Stochastic programming
Swarm intelligence
Visualization of multidimensional data
Web service development
Psychology in multiple criteria decisions

RESEARCH PROJECTS CARRIED OUT IN 2021

Projects Supported by University Budget

Developing Cognitive Computing Capabilities for Data Visualisation, Image Analysis and Decision-Making. Prof. Dr Habil. G. Dzemyda, Prof. Dr O. Kurasova. 2020–2022.

Main publications:

Dzemyda, G., Sabaliauskas, M. Geometric multidimensional scaling: A new approach for data dimensionality reduction. Applied Mathematics and Computation. 2021, 409: 125561. https://doi.org/10.1016/j.amc.2020.125561.

Gudžius, P., Kurasova, O., Darulis, V., Filatovas, E. Deep learning-based object recognition in multispectral satellite imagery for real-time applications. Machine Vision and Applications. 2021, 32(4): 98. DOI: 10.1007/s00138-021-01209-2.

Melnik-Leroy, G.A., Dzemyda, G. How to influence the results of MCDM? – Evidence of the impact of cognitive biases. Mathematics. 2021, 9(2): 121. https://doi.org/10.3390/math9020121.

Melnik, G.A., Peperkamp, S. High-Variability Phonetic Training enhances second language lexical processing: evidence from online training of French learners of English. Bilingualism Language and Cognition. 2021, 1–10. https://doi.org/10.1017/S1366728920000644.

National Research Projects

Research Council of Lithuania. Geometric Method for Solving the Problem of
Multidimensional Scaling (No. MSF-LMT-4). Prof. Dr Habil. G. Dzemyda. 2019–2022.

The main goal of the project is to consider the stress function and multidimensional scaling, in general, the geometric point of view, and to develop the so-called Geometric MDS that creates a basis for a new class of algorithms to minimize the MDS stress. The new interpretation of the stress allows finding the proper step size, and the descent direction forwards the minimum of the stress function analytically if we consider and move a separate point of the projected space.

Main publications:

Dzemyda, G., Sabaliauskas, M. Geometric multidimensional scaling: A new approach for data dimensionality reduction. Applied Mathematics and Computation. 2021, 409: 125561. DOI: 10.1016/j.amc.2020.125561.

Dzemyda, G., Sabaliauskas, M. New capabilities of the geometric multidimensional scaling. In A. Rocha et al. (Eds.): Trends and Applications in Information Systems and Technologies. WorldCIST 2021. Advances in Intelligent Systems and Computing. 2021, 1366: 264–273.

Research Council of Lithuania. Effectiveness and Efficiency Analysis of Education Systems in EU Countries Employing Secondary Big Data (EFECTAS) (No. DOTSUT-39 (09.3.3-LMT-K-712-01-0018) / LSS-250000-57). Dr A. Jakaitienė. 2018–2022.

The main idea of the project is to assess the factors influencing the effectiveness and efficiency of the EU education systems, to develop effectiveness and efficiency measuring instruments in order to implement sound evidence-based educational policy.
The focus of the analysis was on two types of centralised national examinations (the 10th grade tests and Matura examination) that are being carried out in Lithuania for two decades. The purpose of the research is to analyze the assessments of mathematics and the Lithuanian language and literature for the entire Lithuanian secondary school population that do not have sampling errors while considering the factors of location, school ownership, and gender as important indicators when judging educational effectiveness in terms of quality and equity. We analyse the results of the 10th grade tests for the 2011–2015 period and the results of the same cohorts participating in the Matura examination. The conclusions drawn from national assessment data are somewhat different from international data; thus one cannot neglect national information for the development of educational policy. The variables analysed in the analysis have limited predictive power for achievements in both mathematics and the Lithuanian language and literature, and further analysis is required.

Main publications:

Jakaitienė, A., Želvys, R., Vaitekaitis, J., Raižienė, S., ir Dukynaitė, R. Centralised mathematics assessments of Lithuanian secondary school students: population analysis. Informatics in Education. 2021, 20(3): 439–462.

Želvys, R., Raižienė, S., Vaitekaitis, J., Dukynaitė, R., ir Jakaitienė, A. Centralised Lithuanian language and literature assessments of secondary school students: population analysis. Pedagogika. 2021, 141(1): 125–145.

Research Council of Lithuania. Correcting Misperceptions of Covid-19 Mata: an Innovative E-Platform CognitiveSTATS for Training Statistical Intuitions in the General Public (No. 01.2.2-LMT-K-718-05-0042). Dr G. A. Melnik-Leroy. November 2021–September 2023.

The objective of this project is to create a prototype of the innovative e-platform for statistical intuition training in the general public, cognitiveSTATS, which will help to correct misperceptions of Covid-19 data. In order to implement this project, two activities have been planned: 1) to carry out scientific research and experiments in order to identify the most important problems in Covid-19 data interpretation (statistical and/or cognitive) and the most effective ways of training statistical intuitions; 2) based on the results of this research, to develop and test a prototype of the public’s statistical intuition training platform. The platform CognitiveSTATS will help people understand some crucial phenomena inherent to the pandemic situation (the spread of the infection, the effectiveness of safety measures and vaccines, the probability to get infected, the economic consequences of the pandemic etc.) and evaluate more critically data and information, spreading in the public sphere, including those shared on social media. In order to ensure the effectiveness and the attractiveness of the platform, three innovative milestones will be used for its development: evidence from cognitive science, principles of gamification, and visualizations of Covid-19 data. In this way, the project aims at educating the society, training their skills, and as a consequence, significantly influencing the attitudes and behavior of the public. The research carried out during the project and the developed prototype of the e-platform will be presented in international-level scientific articles. Given that the project idea is adaptable to future pandemic or crisis situations and that population attitudes and behavior are an essential factor in managing any emergency situation, CognitiveSTATS has a long-term perspective and can be widely applied in a data-driven world.

MAIN R&D&I (RESEARCH, DEVELOPMENT AND INNOVATION) PARTNERS

University of Almeria (Spain)
University College London (UK)
Bar-Ilan University (Israel)
University of Ferrara (Italy)
Southwestern University of Finance and Economics (China)
Belarus State University (Belorussia)
University of Calabria (Italy)
National Cancer Institute of Lithuania
Hospital of Lithuanian University of Health Sciences Kauno klinikos (Lithuania)
Maribor University (Slovenia)
Vilnius University Hospital Santaros klinikos (Lithuania)
Ecole Normale Supérieure (France)

OTHER RESEARCH ACTIVITIES

Prof. Dr Habil. G. Dzemyda –

  • member of Lithuanian Academy of Science, http://lma.lt;
  • head of Division of Technical Sciences of the Lithuanian Academy of Sciences;
  • member of programme committees of the international conferences:
    o The WorldCist'21 - 9th World Conference on Information Systems and Technologies;
    o ESSE 2021, 2nd European Symposium on Software Engineering;
    o IEEE INISTA 2021, International Conference on INnovations in Intelligent SysTems and Applications (INISTA);
    o SENSORNETS 2021 : 10th International Conference on Sensor Networks;
  • chairman of the 12th International Workshop Data Analysis Methods for Software Systems, Druskininkai, Lithuania, 2021, http://www.mii.lt/DatAMSS/;
  • editor-in-Chief of Baltic Journal of Modern Computing http://www.lu.lv/baltic-journal-of-modern-computing/; international journal Informatica (IOSPress/VU), https://www.mii.lt/Informatica/;
  • editorial board member of 8 international journals: Financial Innovation; International Journal of Computers; Communications and Control; Applied Computer Systems; Informatics in Education; Journal of Civil Engineering and Management; Nonlinear Analysis: Modelling and Control; Mathematics and Informatics. Journal of the Belarusian State University;
  • member of IFIP Technical Committee 12 Artificial Intelligence; http://www.ifiptc12.org.uk/ifiptc12/members.php;
  • member of Lithuanian Computer Society, http://www.liks.lt/;
  • member of Lithuanian Mathematical Society, http://www.mif.vu.lt/lmd/;
  • member of Lithuanian Operational Research Society, http://www.mii.lt/LitORS/.

Prof. Dr O. Kurasova –

Prof. Dr A. Jakaitienė –

Dr R. Karbauskaitė –

Prof. Dr K. Dučinskas –

Dr G. A. Melnik-Leroy –

  • member of the Cognitive Science Society;
  • member of the programme committee of the international conference: New Sounds 2021.


CYBER-SOCIAL SYSTEMS ENGINEERING GROUP

Akademijos 4, LT-08663 Vilnius
Tel. 210 9306
E-mail:
www: https://www.mii.lt/en/structure/scientific-groups/cyber-social-systems-engineering-group
Head – Prof. Dr Saulius Gudas

STAFF

Professor: Prof. Dr S. Gudas.
Senior researcher: Prof. Dr D. Dzemydienė.
Researchers: Dr R. Alonderis, Assoc. Prof. Dr A. Lupeikienė, Dr S. Maskeliūnas.
Research assistants: A. Miliauskas, L. Paliulionienė.
Assistant professors: Dr J. Miliauskaitė, Dr A. Slotkienė.
Afilliated professor: Prof. Dr A. Čaplinskas.
Affiliated researchers: Prof. Dr Habil. S. Jukna, Assoc. Prof. Dr Habil. R. Pliuškevičius, Assoc. Prof. Dr A. Pliuškevičienė.
Doctoral students: V. Radzevičius, K. Noreika.

RESEARCH INTERESTS

Causality driven enterprise application software (EAS) engineering methods:

  • Foundations of causality-based enterprise software engineering
  • Integration of causal models in the MDA / MDD and Agile processes
  • Causal modeling of enterprise management activities and business processes
  • Model based applications and development (MBD) methods for different types of domains (enterprises, Internet of Things, smart systems, etc.)

Mathematical logic:

  • Automated deduction
  • Knowledge analysis methods
  • Deductive systems

RESEARCH PROJECTS CARRIED OUT IN 2021

Projects Supported by University Budget

Research of Cyber-Social Systems and Development of Engineering Methods at the Intersection of Cyber-Physical and Cyber-Social Systems. Prof. Dr S. Gudas (leader), Dr R. Alonderis, Prof. Dr D. Dzemydienė, Assoc. Prof. Dr A. Lupeikienė, Dr S. Maskeliūnas, Dr J. Miliauskaitė, Dr A. Slotkienė, A. Miliauskas, L. Paliulionienė, Affil. Prof. Dr A. Čaplinskas, Affil. Assoc. Prof. Dr Habil. R. Pliuškevičius, Affil. Assoc. Prof. Dr A. Pliuškevičienė, Affil. Habil. Dr S. Jukna, PhD students V. Radzevičius, K. Noreika. 2021–2023.

In 2021, the following main results were obtained: 1) application of domain causality modelling (S. Gudas, K. Noreika, A. Lupeikienė). Modification of the Agile management process by supplementing it with causal models to specify interactions between activities in the Agile hierarchy; 2) a dynamic fuzzification approach for interval type-2 membership function development, a detailed example by modeling service quality characteristics has been provided (J. Miliauskaitė); 3) the methodology for developement of infrastructure of provision smart services and the system architecture on the base of wireless computer networks was proposed, applicable for domains of cargo transportation and monitoring of water resources (D. Dzemydienė, S. Maskeliūnas, A. Miliauskas).

Main publications:

Gudas, S. Causal modelling in enterprise architecture frameworks. Informatica. 2021, 32(2): 247–281. DOI: 10.15388/21-INFOR446.

Kalibatienė, D., Miliauskaitė, J. A dynamic fuzzification approach for interval type-2 membership function development: case study for QoS planning. Soft Computing. 2021, 25(16): 11269–11287. DOI: 10.1007/s00500-021-05899-8.

Kalibatienė, D., Miliauskaitė, J. A hybrid systematic review approach on complexity issues in data-driven fuzzy inference systems development. Informatica. 2021, 32(1): 85–118. DOI: 10.15388/21-INFOR444.

Kalibatienė, D., Miliauskaitė, J., Dzemydienė, D., Maskeliūnas, S. Development of a Fuzzy Inference Based Solar Energy Controller for Smart Marine Water Monitoring. Informatica. 2021, 32: 4. DOI: 10.15388/21-INFOR470.

Dzemydienė, D., Burinskienė, A. Integration of context awareness in smart service provision system based on wireless sensor networks for sustainable cargo transportation. Sensors: Special Issue Artificial Intelligence and Internet of Things in Autonomous Vehicles. 2021, 21(15): 5140. DOI: 10.3390/s21155140.

MAIN R&D&I (RESEARCH, DEVELOPMENT AND INNOVATION) PARTNERS

Riga Technical University (Latvia)
University of Tartu (Estonia)
Warsaw University of Technology (Poland)
Systems Research Institute Polish Academy of Sciences
University of Geneva (Switzerland)
University of Frankfurt (Germany)

OTHER RESEARCH ACTIVITIES

Prof. Dr S. Gudas –

Prof. Dr D. Dzemydienė –

Assoc. Prof. Dr A. Lupeikienė –

  • editorial board member of the Scientific Journal of Riga Technical University: Applied Computer Systems, https://acs-journals.rtu.lv/;
  • steering committee and programme committee member of the 15th International Baltic Conference on Digital Business and Intelligent Systems (Baltic DB&IS 2022), https://dbis2022.lu.lv/about/organisation/;
  • programme committee member of the 14th International Conference on Agents and Artificial Intelligence (ICAART 2022), http://www.icaart.org/.

Dr S. Maskeliūnas –

L. Paliulionienė –

Prof. Dr Habil. S. Jukna –

Assoc. Prof. Dr Habil. R. Pliuškevičius –


EDUCATION SYSTEM GROUP

Akademijos 4, LT-08663 Vilnius
Tel. 210 9732
E-mail:
https://www.mii.lt/struktura/moksliniai-padaliniai/edukaciniu-sistemu-grupe
Head – Prof. Dr Valentina Dagienė

STAFF

Research professor: Prof. Dr V. Dagienė.
Senior researcher: Dr T. Jevsikova.
Researchers: Dr A. Juškevičienė, Dr V. Dolgopolovas.
Other: Dr G. Stupurienė.
Doctoral students: T. Šiaulys, V. Masiulionytė-Dagienė.
Affiliated senior researchers: Assoc. Prof. Dr G. Grigas, Dr L. Markauskaitė.

RESEARCH INTERESTS

Application of intelligent technologies in education
Computer science (Informatics) education research
Computing engineering education research
Software localisation
Technology enhanced learning

RESEARCH THEME FOR 2021-2023:

Research on Educational Environments and Technologies to Improve the Quality of Education. Prof. Dr V. Dagienė. 2021–2023.

Main objective of the theme is to study the problems of designing, integrating and personalising interactive educational environments and technologies in education.

Main publications:

Jevsikova, T., Stupurienė, G., Stumbrienė, D., Juškevičienė, A., Dagienė, V. Acceptance of distance learning technologies by teachers: determining factors and emergency state influence. Informatica. 2021, 32(3): 517–542. DOI: 10.15388/21-INFOR459.

Juškevičienė, A., Dagienė, V., Dolgopolovas, V. Integrated activities in STEM environment: methodology and implementation practice. Computer Applications in Engineering Education. 2021, 29(1): 209–228. DOI: 10.1002/cae.22324.

Juškevičienė, A., Stupurienė, G., Jevsikova, T. Computational thinking development through physical computing activities in STEAM education. Computer Applications in Engineering Education: Special Issue: Computational thinking: Enhancing STEAM and engineering education, from theory to practice. 2021, 29(1): 175–190. DOI: 10.1002/cae.22365.

International Research Projects

COST: EUGAIN - CA19122. European Network for Gender Balance in Informatics. Dr V. Dagienė, Dr A. Juškevičienė. 2020–2024.

Research Council of Lithuania. Using Constructivism, and Project and Challenge Driven Pedagogy for Learning Computational Thinking. Dr A. Juškevičienė. 2020–2021.

MAIN R&D&I (RESEARCH, DEVELOPMENT AND INNOVATION) PARTNERS

Ankara University (Turkey)
ETH Zurich (Switzerland)
Lancaster University (UK)
Radboud University Nijmegen (The Netherlands)
Turku University (Finland)

OTHER RESEARCH ACTIVITIES

Prof. Dr V. Dagienė –

Dr V. Dolgopolovas –

Dr T. Jevsikova –

  • member of International Federation for Information Processing (IFIP) TC3 WG 3.1 (Informatics for Secondary Education).

Dr G. Stupurienė –

MOST IMPORTANT RESEARCH DISSEMINATION ACTIVITIES

  • Valentina Dagienė, Gabrielė Stupurienė, Tatjana Jevsikova. Methodological materials for teachers, organisation of International Challenge on Informatics and Computational Thinking “Bebras”.
  • V. Dagienė. The international Bebras conference, Druskininkai (remotely), with over 60 countries participating.
  • The International Computer Science Olympiad in Singapore (remotely). V. Dagienė - member of the International Committee.
  • International journal Informatics in Education Scopus citation index 3.3 (2020 year), preliminary index of 2021 year – 3.8. WoS Journal Citation Indicator – 1.24 (not final).
  • Tatjana Jevsikova and Anita Juškevičienė. Methodologies for the Vilnius STEAM Centre, Laboratory of Robotics and Mobile Computing and Laboratory of Visual Programming.


GLOBAL OPTIMIZATION GROUP

Akademijos 4, LT-08663 Vilnius
Tel. 210 9304
E-mail:
Head – Prof. Dr Julius Žilinskas

STAFF

Research professors: Prof. Dr J. Žilinskas, Prof. Dr Habil. A. Žilinskas.
Senior researchers: Assoc. Prof. Dr A. Lančinskas, Assoc. Prof. Dr R. Pupeikis.
Doctoral students: S. Tautvaišas, M. Kepalas.

RESEARCH INTERESTS

Optimization and high-performance computing

RESEARCH PROJECTS CARRIED OUT IN 2021

Projects Supported by University Budget

Global Optimization. Prof. Dr J. Žilinskas.

The aim is development of global optimization algorithms and application of them to optimization problems.
The main results were: global optimization algorithms with constraints; heuristic algorithms for facility location problems; Bayesian global optimization; linear convolution computations online optimization algorithm.

Main publications:

Pupeikis, R. Joint tracking coefficients and the time delay of a nonstationary linear system preceded by a static nonlinearity. International Journal of Adaptive Control and Signal Processing. 2021, 35(6): 941–964. DOI: 10.1002/acs.3233.

Žilinskas, J., Lančinskas, A. & Guarracino, M. R. Pooled testing with replication as a mass testing strategy for the COVID-19 pandemics. Sci Rep. 2021, 11: 3459. https://doi.org/10.1038/s41598-021-83104-4.

Zhigljavsky, A., Žilinskas, A. Bayesian and High-Dimensional Global Optimization. 2021, 118 p. DOI: 10.1007/978-3-030-64712-4.

National Research Projects

LMT MIP. Solution of Competitive Facility Location Problems with Constraints Using High Performance Computing Systems. A. Lančinskas.

International Research Projects

COST action. Randomised Optimization Algorithms Research Network. A. Lančinskas.

COST action. The European Network for Data-Driven Decision Making. J. Žilinskas.

MAIN RESEARCH ACHIEVEMENTS IN 2021

Heuristic algorithms for facility location problems
Bayesian global optimization
Linear convolution computations real time optimization algorithm

MAIN R&D&I (RESEARCH, DEVELOPMENT AND INNOVATION) PARTNERS

Universidad de Almería (Spain)
Universidad de Murcia (Spain)
Universidad de La Laguna (Spain)
University of Edinburgh (UK)
Università della Calabria (Italy)
Università degli Studi di Cassino e del Lazio Meridionale (Italy)
Cardiff University (UK)
New Jersey Institute of Technology (USA)

OTHER RESEARCH ACTIVITIES

Prof. Dr J. Žilinskas –

Prof. Dr Habil. A. Žilinskas –

Dr A. Lančinskas –

  • affiliate member of European Network of Excellence on High Performance and Embedded Architecture and Compilation (HiPEAC), http://www.hipeac.net.


IMAGE AND SIGNAL ANALYSIS GROUP

Akademijos 4, LT-08663 Vilnius
Tel. 210 9328
E-mail:
Head – Assoc. Prof. Dr Povilas Treigys

STAFF

Senior researchers: Assoc. Prof. Dr P. Treigys, Dr G. Korvel, Assoc. Prof. Dr G. Tamulevičius, Dr J. Bernatavičienė.
Affiliated researchers: Prof. Dr Habil. K. Kazlauskas, Prof. Dr Habil. A. L. Telksnys.
Projects specialist: G. Navickas.
Specialist: S. Virbukaitė.
Doctoral students: B. Čiapas, J. Jucevičius, S. Virbukaitė, M. Danilovaitė, R. Jurkus, A. Vaitulevičius.
Study staff: L. Aidokas, A. Rasmusson, J. Globienė, M. Liutvinavičius.

RESEARCH INTERESTS

Audio and image signal processing; patern recognition; robotics; machine learning; natural language processing; machine learning.

RESEARCH PROJECTS CARRIED OUT IN 2021

Projects Supported by University Budget

Digital Signal Analysis and Modelling.

Tasks in 2021 were: to develop deep learning models for sea traffic anomaly detection, to develop autoencoder based collagen network extraction deep learning model in WSI images, to investigate deep learning models for Lombard effect analysis, to prepare prostate MRI cancerous zones detection application, to develop short period forecast model of COVID-19 infection spread.

Main results were: semi-supervised and unsupervised machine learning methods for sea traffic anomaly detection and tumour microenvironment-oriented digital pathology methods for whole slide image segmentation and classification developed, Lombard speech models in the context of speech in noise enhancement evalued, application prepared and submitted for funding, attention-based and time series models for short-term forecasting of COVID-19 spread developed.

Main publications:

Morkūnas, M., Žilėnaitė, D., Laurinavičienė, A., Treigys, P., Laurinavičius, A. Tumor collagen framework from bright-field histology images predicts overall survival of breast carcinoma patients. Scientific Reports. 2021, 11(1): 15474. DOI: 10.1038/s41598-021-94862-6.

Korvel, G., Treigys, P., Kostek, B. Highlighting interlanguage phoneme differences based on similarity matrices and convolutional neural network. Journal of the Acoustical Society of America. 2021, 149(1): 508–523. DOI: 10.1121/10.0003339.

Markevičiūtė, J., Bernatavičienė, J., Levulienė, R., Medvedev, V., Treigys, P., Venskus, J. Attention-based and time series models for short-term forecasting of COVID-19 spread. CMC-Computers, Materials & Continua. 2022, 70(1): 695–714. DOI: 10.32604/cmc.2022.018735.

National Research Projects

Vilnius Region Biomedical Research Committee. Nuasmenintų akių dugnų vaizdų bazės kūrimas [Developing database of images of depersonalised bottoms of eyes] (no. 158200-18/11-1057-572). November 2018–October 2030.

Postdoctoral project Investigating Speech in the Presence of Noise Interferences Employing Signal Processing and Machine Learning Methods. August 2021–August 2023.

International Research Projects

H2020National Competence Centres in the Framework of EuroHPC (951732). 01 September 2020–31 August 2022.

Within the EuroCC project under the European Union’s Horizon 2020 (H2020), participating countries are tasked with establishing a single National Competence Centre (NCC) in the area of high-performance computing (HPC) in their respective countries. These NCCs will coordinate activities in all HPC-related fields at the national level and serve as a contact point for customers from industry, science, (future) HPC experts, and the general public alike. The EuroCC project is funded 50 percent through H2020 (EuroHPC Joint Undertaking [JU]) and 50 percent through national funding programs within the partner countries. The EuroCC activities, with 33 member and associated countries on board, are coordinated by the High-Performance Computing Center Stuttgart (HLRS). The project aims to elevate the participating countries to a common high level in the fields of HPC, HPDA and artificial intelligence (AI). To this end, the EuroCC project will establish National Competence Centres (NCCs) in the participating countries, which will be responsible for surveying and documenting the core HPC, HPDA, and AI activities and competencies in their respective countries. Ultimately, the goal is to make HPC available to different users from science, industry, public administration, and society.

COST action CA18231. Multi3Generation: Multi-task, Multilingual, Multi-modal Language Generation. Member of Managing Committee Dr G. Korvel. 2019–2023.

Language generation (LG) is a crucial technology if machines are to communicate with humans seamlessly using human natural language. A great number of different tasks within Natural Language Processing (NLP) are language generation tasks, and being able to effectively perform these tasks implies (1) that machines are equipped with world knowledge that can require multi-modal processing and reasoning (e.g. textual, visual and auditory inputs, or sensory data streams), and (2) the study of strong, novel Machine Learning (ML) methods (e.g. structured prediction, generative models), since virtually all state-of-the-art NLP models are learned from data. Moreover, human languages can differ wildly in their surface realisation (i.e. scripts) as well as their internal structure (i.e. grammar), which suggests that multilinguality is a central goal if machines are to perform seamless language generation. Language generation technologies would greatly benefit both public and private services offered to EU citizens in a multilingual Europe and have strong economic and societal impacts.

Main results are: machine learning algorithms for tumour classification, feature space analysis for machine based recognition, machine learning algorithms for multiscale data analysis, machine learning methods for language generation, and efficient deployment of fractal theory to industry applications.

MAIN R&D&I (RESEARCH, DEVELOPMENT AND INNOVATION) PARTNERS

Hospital Kauno klinikos of Lithuanian University of Health Sciences (Lithuania)
Vilnius University Hospital Santaros klinikos (Lithuania)
National Cancer Institute (Lithuania)
Brno University of Technology (Czech Republic)
Gdansk University of Technology, Faculty of Electronics, Telecommunications and Informatics, Audio Acoustics Laboratory (Poland)
Aveiro University (Portugal)

OTHER RESEARCH ACTIVITIES

Prof. Dr Habil. A. L. Telksnys –

Prof. Dr Habil. K. Kazlauskas –

Assoc. Prof. Dr G. Tamulevičius –

  • member of IEEE Computer Society and Signal Processing Society sections.

Dr G. Korvel –

Dr J. Bernatavičienė –

G. Navickas –


INTELLIGENT TECHNOLOGIES RESEARCH GROUP

Akademijos 4, LT-08663 Vilnius.
Tel. 210 9311
E-mail:
Head – Dr Virginijus Marcinkevičius

STAFF

Senior researchers: Dr V. Marcinkevičius, Prof. Dr S. Minkevičius, Prof. Dr D. Plikynas, Prof. Dr I. Belovas.
Affiliated researchers: Prof. Dr Habil. L. Sakalauskas, Dr S. Steišūnas.
Research assistant: A. Chaževskas.
Doctoral students: A. Chaževskas, V. Dulskis, R. Gricius, P. Šiktorov, M. Stankevičius, N. Urbonaitė, P. Vaitkevičius.

RESEARCH INTERESTS
Machine learning and its application
Artificial intelligence and its application
Natural language processing
Cyber security
Mathematical modelling
Image analysis
Data mining and visualization
Application of modeling, classification and clustering methods in medicine (e.g. in genetics) and economics
Optimization. Application of stochastic optimization methods in engineering
Multi-agent systems: simulation and application in social research

RESEARCH PROJECTS CARRIED OUT IN 2021

National Research Projects

Integruotų lietuvių kalbos ir raštijos išteklių informacinės sistemos plėtra – Raštija 2 [Information System Development of Integrated Lithuanian Language, Oral and Written, Sources. Dr Virginijus Marcinkevičius. 2018–2021.

Main goal is development of the measuring metrics, conceptual and agent-based simulation model aimed at investigation of the social impact of cultural processes.

Main results are: 1) new algorithms for 3D simulation and visualization of Riemann zeta function; 2) experimental analysis of algorithms using ensembles of recurrent neural networks to detect phishing websites; 3) a model for queueing networks consisting of 100 subnets under high load conditions; 4) LMT research group project No. P-MIP-17-368 Kultūros procesų socialinio poveikio metrikos, konceptualaus bei imitacinio modelio kūrimas [Development of metrics, conceptual and simulation models of the social impact of cultural processes] completed.

Main publications:

Belovas, I. Central and local limit theorems for numbers of the tribonacci triangle. Mathematics. 2021, 9(8): 880. https://doi.org/10.3390/math9080880.

Bulavas, V., Marcinkevičius, V., Ruminski, J. Study of multi-class classification algorithms' performance on highly imbalanced network intrusion datasets. Informatica. 2021, 32(3): 441–475.

Belovas, I. An inequality for the modified Selberg zeta-function. Ramanujan Journal. 2021, 55(3): 1063–1082.

MAIN R&D&I (RESEARCH, DEVELOPMENT AND INNOVATION) PARTNERS

SAP (Germany)
Neurotechnology (Lithuania)
University of Tartu (Estonia)
Vilnius Gediminas Technical University (Lithuania)
Ghent University (Belgium)
Warsaw University of Technology (Poland)
Lithuanian Culture Research Institute (Lithuania)

OTHER RESEARCH ACTIVITIES

Prof. L. Sakalauskas –

Prof. D. Plikynas -

  • member of Artificial Intelligence section of Lithuanian Computer Society (LIKS-AIS);
  • member of ESSA (European Social Simulation Association);
  • member of ECCAI (European Coordinating Committee for Artificial Intelligence).

Assoc. Prof. Dr I. Belovas –

Prof. Dr S. Minkevičius –

member of Lithuanian Mathematical Society, http://www.mif.vu.lt/lmd/.

Dr V. Marcinkevičius –


STATISTICS AND PROBABILITY GROUP

Akademijos 4, LT-08663 Vilnius
Tel. 210 9731
E-mail:
Head – Prof. Dr Habil. Kęstutis Kubilius

STAFF

Research professors: Prof. Dr Habil. K. Kubilius, Dr S. Norvidas.
Professor: Prof. Dr Habil. M. Sapagovas (emeritus).
Senior researchers: Dr D. E. Otera, Dr M. Radavičius, Dr M. Vaičiulis.
Researchers: Dr A. Astrauskas Dr A. Bakšaev, Dr A. Čiginas, Dr V. Kurauskas,
Dr J. Novickij.
Affiliated researchers: Dr J. J. Mačys, Prof. Dr R. Mikulevičius, Prof. Dr Habil. R. Rudzkis, Prof. Dr Habil. J. K. Sunklodas.
Doctoral student: A. Medžiūnas.

RESEARCH INTERESTS

Statistical inference for long memory processes
Heavy tails
Self-similar processes
Rough paths
Finite population statistics and statistical analysis of data
Extremal problems in harmonic analysis
Differential equations with an integral boundary condition
Random graphs
Combinatorics
Discrete mathematics
Algebraic geometry

RESEARCH PROJECTS CARRIED OUT IN 2021

Projects Supported by University Budget

Analysis and Application of Probabilistic and Deterministic Models. Prof. Dr Habil. K. Kubilius. 2020–2021.

The problem of large excursions of the random fields close to Gaussian ones are considered.
The conditions of proximity to a Gaussian field are stated in terms of cumulants. These conditions are easily verified for a broad class of empirical processes and fields.
A class of fractional stochastic differential equations (FSDEs) with coefficients that may not satisfy the linear growth condition and non-Lipschitz diffusion coefficient are considered. The almost sure convergence rate of the backward Euler approximation scheme for solutions of the considered SDEs is obtained. A strongly consistent and asymptotically normal estimator of the Hurst index H>1/2 for positive solutions of FSDEs is proposed.

The non-permutability graph of subgroups, which generalizes the permutability graph of subgroups, and that is a graph constructed from (a subspace of) the subgroups lattice are studied. Its planarity for some specific classes of groups are studied.

Main publications:

Rudzkis, R., Bakšajev, A. Large excursion probabilities for random fields close to Gaussian ones. Extremes. 2021, 24(3): 591–615. DOI: 10.1007/s10687-021-00411-9.

Kubilius, K., Medžiūnas, A. Positive solutions of the fractional SDEs with non-Lipschitz diffusion coefficient. Mathematics. 2021, 9(1): 18. DOI: 10.3390/math9010018.

Muhie, S. K., Otera, D. E., Russo, F. G. Non-permutability graph of subgroups. Bulletin of the Malaysian Mathematical Sciences Society. 2021, 44(6): 3875–3894. DOI: 10.1007/s40840-021-01146-3.

OTHER RESEARCH ACTIVITIES

Prof. K. Kubilius –

Prof. S. Norvidas –

Affiliated Prof. R. Rudzkis –

  • member of the Board of the Research Council of Lithuania.

Prof. Emeritus M. Sapagovas –


ARTIFICIAL INTELLIGENCE LABORATORY

Akademijos 4, LT-08663 Vilnius.
Tel. 210 9311
E-mail:
Head – Dr Virginijus Marcinkevičius

STAFF

Senior researcher: Dr V. Marcinkevičius.
Research assistants: Dr J. Vaičiulytė, L. Aidokas.
Other staff: N. Urbonaitė.
Doctoral students: S. Juneja, V. Paura.

RESEARCH INTERESTS

Advance machine learning in process automatization
Natural language processing
Image processing and analysis with deep neural networks
Visual odometry and localization

RESEARCH PROJECTS CARRIED OUT IN 2021

National Research Projects

The main goal is to investigate machine and imitational learning usage for robot navigation and localization in real environments. Research of natural language processing applications in human-machine interface

Main results:

Bulavas, V., Marcinkevičius, V., Ruminski, J. Study of multi-class classification algorithms' performance on highly imbalanced network intrusion datasets. Informatica. 2021, 32(3): 441–475.

Jurgelevičius, A., Sakalauskas, L., Marcinkevičius, V. Application of a Task Stalling Buffer in Distributed Hybrid Cloud Computing. Elektronika ir Elektrotechnika. 2021, 27(6): 57–65.

MAIN R&D&I (RESEARCH, DEVELOPMENT AND INNOVATION) PARTNERS

SAP (Germany)
Neurotechnology (Lithuania)

OTHER RESEARCH ACTIVITIES

Dr V. Marcinkevičius –

 
INSTITUTE OF COMPUTER SCIENCE

Didlaukio 47, LT-08303 Vilnius
Tel. 219 5040
E-mail:
www: https://mif.vu.lt/lt3/en/about/structure/institute-of-computer-science
Director – Prof. Dr Rimantas Vaicekauskas

DEPARTMENTS AND LABORATORIES OF THE INSTITUTE

Department of Computational and Data Modeling
Department of Computer Science
Department of Mathematical Computer Science
Department of Software Engineering
Cybersecurity Laboratory

RESEARCH AREAS

Informatics
Informatics engineering
Fundamental mathematics
Applied mathematics

BEST REPORTS DELIVERED AT CONFERENCES ABROAD

  • Jurevičienė A., Brilingaitė A., Bukauskas L. Digital Human in Cybersecurity Risk Assessment. In: Schmorrow D.D., Fidopiastis C.M. (eds) Augmented Cognition. HCII 2021. Lecture Notes in Computer Science, vol 12776. https://doi.org/10.1007/978-3-030-78114-9_29.

MAIN SCIENTIFIC ACHIEVEMENTS IN 2021

Monograph Mathematical Modeling of Biosensors. 2nd edition (Springer, 2021) authored by R. Baronas, F. Ivanauskas, J. Kulys covers the mathematical aspects and presents unique digital modeling methods for a wide range of biosensors. It is great compendium of biosensor modelling and development for researchers in both chemistry and mathematics.

Application of formal methods to automated verification of well-formedness and semantic correctness of data sets from the railway domain has been investigated. Novel validation approach based on statistical testing of automatically generated verification conditions against pre-validated data sets was developed.

It was demonstrated that AI (Artificial Intelligence) based AFM (Atomic Force Microscopy) image analysis allows to predict EIS (Electrochemical Impedance Spectra) of defects in tethered bilayer membranes.

A photosensitization phenomenon application reviewed for the development of innovative non-thermal, cost effective and sustainable antimicrobial technology, saving water and energy.

Novel framework to combine the learnable modules to follow trajectories from data to graph-based topology for autonomous navigation was developed.


DEPARTMENT OF COMPUTATIONAL AND DATA MODELING

Didlaukio 47, LT-08303 Vilnius
Tel. 219 5020
E-mail: ,
Head – Assoc. Prof. Dr Rimvydas Krasauskas

STAFF

Professors: Dr Habil. Emeritus F. Ivanauskas, Dr A. Juozapavičius (part-time), Dr T. Meškauskas.
Associate professors: Dr A. Brilingaitė, Dr L. Bukauskas, Dr P. Kasparaitis, Dr R. Krasauskas, Dr V. Rapševičius (part-time), Dr S. Zubė.
Senior researcher: Dr. S. Šaltenis.
Researchers: Dr A. Barauskas, Dr V. Čeikutė.
Assistant professors: Dr R. Astrauskas, Dr M. Beniušė, Dr A. Čivilis (part-time), Dr J. Katina, Dr A. V. Misiukas Misiūnas (part-time).
Teaching assistants: T. Raila (part-time), J. M. Menjanahary.
Lecturers: Dr J. Ignatavičiūtė, L. Būtėnas (part-time), V. Krinickij, E. Kutka (part-time), V. Masiulionytė-Dagienė (part-time), G. Šamrickis (part-time), B. Šulmanas (part-time).
Associate professors of practice: T. G. Lipnevičius (part-time), R. Markauskas (part-time).
Doctoral students: S. Bucka, T. Raila.

RESEARCH INTERESTS

Methods and applications of nonlinear and computational modeling, computational geometry
Methods of computer vision, medical imaging, digital imaging, speech and signal processing, data structures and algorithms
Computational modeling of chemical, electrochemical, medical, biological processes and systems
Internet technology and information systems
Location based services and database management systems
Algorithms for intelligent transport
Computer networks
Cloud and parallel computing, virtualization
Education in computer science

RESEARCH PROJECTS CARRIED OUT IN 2021

Projects Supported by University Budget

Research and Application of Methods for Computational and Geometric Modeling, Images, Signals and Databases Analysis. Dr T. Meškauskas, Dr R. Krasauskas. 2019–2023.

The monograph “Mathematical modeling of biosensors. Second edition” covers the mathematical aspects and presents unique digital modeling methods for a wide range of biosensors. It is great compendium of biosensor modelling and development for researchers in both chemistry and mathematics. Employing machine learning type methods, automatic processing of AFM (atomic force microscopy) images was researched.

Lithuanian text-to-speech synthesizer based on the Tacotron 2 deep neural network package was implemented. Rational parametrizations of cyclide surfaces and their applications for spline constructions were investigated.
Little’s formula in multiphase queues using own developed software model was investigated.
Imaging of internal structure and quantum dots distribution in chorion of rainbow trout Oncorhynchus mykiss live embryos: towards understanding of potential nanotoxicity.

Main publications:

Baronas, R., Ivanauskas, F., Kulys, J. Mathematical modeling of biosensors. Second edition. 2021. 473 p. DOI: 10.1007/978-3-030-65505-1.

Dabulyte-Bagdonaviciene, J., Neciporenko, A., Ivanauskas, F., Kareiva, A. Influence of different diffusion rates of reaction reagents on the synthesis of yttrium aluminium garnet (YAG). Journal of Mathematical Chemistry. 2021. DOI: 10.1007/s10910-021-01303-w.

Jurgelėnė, Ž., Stankevičius, M., Stankevičiūtė, M., Kazlauskienė, N., Katauskis, P., Ivanauskas,F., Karabanovas, V., Rotomskis, R. Imaging of the internal chorion structure of rainbow trout Oncorhynchus mykiss live embryos and the distribution of quantum dots therein: Towards a deeper understanding of potential nanotoxicity. Science of the Total Environment. 2021, 785: 1473022. DOI: 10.1016/j.scitotenv.2021.147302.

National Research Projects

Research Council of Lithuania. Quantitative Assessment of the Membrane Damage By the Pore-Forming Toxins (No. LMT S-MIP-19-33). Project leader Dr G. Valinčius, Life Sciences Center, Vilnius University, Dr T. Meškauskas and T. Raila. 2019–2022.

It was demonstrated that AI (Artificial Intelligence) based AFM (Atomic Force Microscopy) image analysis allows to predict EIS (Electrochemical Impedance Spectra) of defects in tethered bilayer membranes.

Research Council of Lithuania. Data Management and Algorithms for Smart Transportation (No. 01.2.2-LMT-K-718-02-0018). Project leader Dr S. Šaltenis, Dr A. Brilingaitė, Dr L. Bukauskas, Dr A. Čivilis, E. Kutka, V. Krinickij. 2019–2023.

The data model of charge-arrival-time profiles and testbed was proposed to capture long electric vehicle routes and compare travel plans for trips with charging stops.

Main publications:

Petkevičius, L., Šaltenis, S., Čivilis, A., Torp, K. Electric vehicle energy consumption modelling and estimation, DAMSS: 12th conference on Data analysis methods for software systems, Druskininkai, Lithuania, 2–4 December, 2021, p. 57. DOI: 10.15388/DAMSS.12.2021.

Petkevičius, L., Šaltenis, S. Čivilis, A., Torp, K. Probabilistic deep learning for electric-vehicle energy-use prediction, SSTD '21: 17th international symposium on spatial and temporal databases: virtual, USA, 23–25 August 2021, p. 85-95. DOI: 10.1145/3469830.3470915.

Barauskas, A., Brilingaitė, A., Bukauskas, L., Čeikutė, V., Čivilis, A., Šaltenis, S. Semi-synthetic data and testbed for long-distance E-vehicle routing, New trends in database and information systems - {ADBIS} 2021 short papers, doctoral consortium and workshops: DOING, SIMPDA, MADEISD, MegaData, CAoNS, Tartu, Estonia, 24–26 August 2021, p. 61-71. (Communications in Computer and Information Science book series, vol. 1450). DOI: 10.1007/978-3-030-85082-1_6.

International Research Projects

EU Horizon 2020 (EOSC-Nordic project funded by H2020). Leading Nordforsk. Dr A. Brilingaitė, Dr L. Bukauskas and E. Kutka. 2019–2022.

European open science cloud infrastructure as a service was investigated and considered with local legal context.

EU Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Actions – Innovative Training Networks (ITN) funding scheme (H2020-MSCA-ITN-2019). GRAPES – Learning, Processing and Optimising Shapes (No. 860843). Project coordinator: Prof. I. Emiris, ATHENA RIC, Greece, Dr R. Krasauskas and Dr S. Zubė. 2019–2023.

This is a multidisciplinary consortium uniting 17 academic institutions and industrial partners all around Europe. The VU team is developing cyclidic splines of arbitrary topology based on circular meshes and Dupin cyclide surfaces.

MAIN R&D&I (RESEARCH, DEVELOPMENT AND INNOVATION) PARTNERS

Aalborg University (Denmark)
CERN (Switzerland)
Financial Crime Investigation Service (Lithuania)
ART21, JSC (Lithuania)

OTHER RESEARCH ACTIVITIES

Prof. Emeritus F. Ivanauskas –

Prof. A. Juozapavičius –

Assoc. Prof. A. Brilingaitė –

Assoc. Prof. L. Bukauskas –

  • Board member of Technical Committee No. 86 for Digital geographic information at the Department of Standardization.

Assoc. Prof. R. Krasauskas –

BEST REPORTS DELIVERED AT CONFERENCES ABROAD

  • R. Krasauskas, Cyclidic splines and kinematic interpretation of quaternionic curves and surfaces. Dagstuhl Seminar 21471, Geometric Modeling: Interoperability and New Challenges, 21–26 November 2021, Dagstuhl, Germany.


DEPARTMENT OF COMPUTER SCIENCE

Didlaukio 47, LT- 08303 Vilnius
Tel. 219 5001
E-mail:
Head- Prof. Dr Rimantas Vaicekauskas

STAFF

Professors: Dr R. Vaicekauskas, Dr L. Laibinis (part-time), Dr A. Raudys (part-time).
Researcher: Dr L. Laibinis (part-time).
Senior researcher: Dr Habil. Š. Raudys.
Assistant professors: Dr J. Andrikonis, Dr A. Birštunas, Dr V. Dičiūnas, Dr H. Giedra, Dr L. Litvinas, Dr G. Skersys.
Professors of practice: Dr D. Baronas (part- time), Dr R. Kybartas (part-time).
Associate professors of practice: S. Grigaitis (part- time), A. Janeliūnas (part-time), R. Masiulis (part-time), L. Ričkus (part-time).
Lecturers: S. Blažiūnas (part-time), Dr R. Dzindzalieta (part-time), M. Grubliauskis (part- time), K. Mizara (part-time), I. Radavičius.

RESEARCH INTERESTS

Formal modelling and verification of distributed software-based systems
Quantitative assessment of complex computer-based systems
Automated formal reasoning about system correctness using interactive proof assistants
Combinatorial search in large number theory problems
Colour rendering of light sources and its applications
Global optimization of multi-objective functions
Computational modelling and optimisation of bioreactors
Qualified electronic signature and applications
Error-correcting codes
Computational intelligence and machine learning
Financial data analysis using computational intelligence methods
Temporal and modal logics
Buridan’s divided modal propositions
Neural networks, pattern recognition

RESEARCH PROJECTS CARRIED OUT IN 2021

Projects Supported by University Budget

Development of Intelligence Methods and its Applications in Information Technologies. Prof. R. Vaicekauskas, Dr L. Laibinis, Dr A. Raudys. 2021–2025.

Application of formal methods to automated verification of well-formedness and semantic correctness of data sets from the railway domain has been investigated. Novel validation approach based on statistical testing of automatically generated verification conditions against pre-validated data sets was developed.

Gentzen type sequent calculus for logic of propositional linear temporal logic with the operators “next” and “until” was developed. Buridan’s divided modal propositions were formalized using quantified modal logic.

New sound and complete inference method for propositional logic ensuring traceability feature was introduced.

Main publications:

Dagys, J., Pabijutaitė, Ž., Giedra, H. Representing Buridan’s divided modal propositions in first- order logic. History and Philosophy of Logic. 2021, first published online. DOI: 10.1080/01445340.2021.1976042.

Laibinis, L., Iliasov, A., Romanovsky, A. Mutation testing for rule-based verification of railway signaling data. IEEE Transactions on Reliability. 2021, 70(2): 676–691. DOI: 10.1109/TR.2020.3047462.

Radzevičius, A., Raudys, A., Kasparaitis, P. Speech Synthesis Using Stressed Sample Labels for Languages with Higher Degree of Phonemic Orthography. Information and Software Technologies. Communications in Computer and Information Science. 2021, 1486: 378–387.

National Research Projects

Investigation of Traditional Logic of Modalities Using Modern Logic Theories and Information Technology, No P-MIP-19-51. 2019–2022.

Representation of Buridan’s divided modal propositions was achieved in the research, which relies on the use of actualist quantification over variable domains. The formulas adequately capture truth conditions given by Buridan, and they preserve all relations of the octagon, as well as permissible conversions in modal S5.

Contractual Research

Contractual research for business project: Airspace Planning and Analysis (No. (1.57) 15600-INS-65). Prof. R. Vaicekauskas (proj. leader), Dr Linas Petkevičius, Dr Audrius Indriulionis. 2020–2021.

The novel deep learning algorithms were developed to solve finding of the optimal flight service configurations, as well as proposed end-to-end optimization technique of scheduling of air traffic controllers’ problem.

MAIN R&D&I (RESEARCH, DEVELOPMENT AND INNOVATION) PARTNERS

Pattern recognition and Applications LAB, Department of Electrical and Electronic Engineering, University of Cagliari (Italy)
University of Granada (Spain)
Department of Economics and Finance, LUISS Guido Carli, Rome (Italy)
School of Computing, Newcastle University (UK)
Office of the Government of the Republic of Lithuania
Elsis PRO (a Novian company) - leading provider of software solutions for defense, airspace, healthcare domains
The Formal Route Ltd (UK) - tool developer company for mathematical modelling and safety verification of railway signalling designs

OTHER RESEARCH ACTIVITIES

Prof. Dr Habil. Š. Raudys –

Prof. L. Laibinis –

  • program committee member of the International Workshop on Software Engineering for Resilient Systems (SERENE).

MOST IMPORTANT PARTICIPATION CASES OF RESEARCHERS IN WORKING GROUPS OR COMMISSIONS SET UP BY STATE AUTHORITIES, STATE AND MUNICIPAL INSTITUTIONS AND ORGANISATIONS, AND BUSINESS ENTITIES

  • Prof. R. Vaicekauskas: member of EnergyTech Digital group of association INFOBALT (representative of Lithuanian ICT industry). The association has more than 160 members, including national and global businesses, universities, colleges and research institutions involved in ICT education, employing more than 10,000 experienced ICT professionals, teachers and researchers.

CONSULTATIONS PROVIDED BY THE UNIT TO THE PUBLIC OR ECONOMIC ENTITIES

Prof. A. Raudys – Researcher-consultant in a business project:

  • The smart home repair system is based on self-learning technologies.
  • Dizozols SIA R&D investment project for the development of innovative products.
  • Creating innovative real estate platforms based on artificial intelligence.
  • Intelligent heat distribution and production optimization system.
  • Development of Smart Bus Size and Schedule Optimization System.
  • Development of SME Credit Risk Prediction System.


DEPARTMENT OF MATHEMATICAL COMPUTER SCIENCE

Didlaukio 47, LT-08303 Vilnius
Tel. 219 5030
Email:
Head – Assoc. Prof. Dr Gintautas Bareikis

STAFF

Professors: Dr Habil. M. Bloznelis, Dr S. Gražulis (part-time), Dr Habil. Ž. Lukšienė (part-time).
Associate professors: Dr G. Bareikis, Dr A. Mačiulis, Dr V. Stakėnas, Dr V. Zacharovas.
Lecturer: I. Grinis.
Researcher: Dr G. Alkauskas.
Doctoral student: D. Ardickas

RESEARCH INTERESTS

Probabilistic analysis of number-theoretical structures
Combinatorial statistics
Random discrete structures and algorithms

RESEARCH PROJECTS CARRIED OUT IN 2021

Projects Supported by University Budget

Analysis of Discrete Structures by Probabilistic, Combinatorial and Analytical Methods.
Prof. M. Bloznelis, Assoc. Prof. A. Mačiulis. 2017–2022.

A photosensitization phenomenon application reviewed for the development of innovative non-thermal, cost effective and sustainable antimicrobial technology, saving water and energy.
Sieve asymptotics for Farey fractions is obtained, new mean value theorem for multiplicative functions with rational argument is proved.

A two dimensional Dirichlet distribution for any set of parameters was modeled by means of the sequences of distributions related to the generalized divisors function.

Main publications:

Bareikis, G., Mačiulis, A. Bivariate Beta distribution and multiplicative functions. European Journal of Mathematics. 2021, 7(4): 1668–1688.

Lukšienė, Ž. Photosensitization: principles and ivilapplications in food processing. Innovative Food Processing Technologies: A Comprehensive Review. Vol. 2, Kai Knoerzer, Kasiviswanathan Muthukumarappan (Eds.). 2021, 2.24: 368–384.

Stakėnas, V. Sieving the rationals. Lithuanian Mathematical Journal. 2021, 61(3): 401–412.

MAIN R&D&I (RESEARCH, DEVELOPMENT AND INNOVATION) PARTNERS

Aalto University (Finland)
Poznan Adam Mickiewicz University (Poland)
Bielefeld University (Germany)

OTHER RESEARCH ACTIVITIES

Dr G. Alkauskas –

Assoc. Prof. G. Bareikis –

Prof. M. Bloznelis –

Assoc. Prof. A. Mačiulis –

Assoc. Prof. V. Stakėnas –

MOST IMPORTANT RESEARCH DISSEMINATION ACTIVITIES

  • Dr G. Alkauskas. TV program about Hermann Minkowski on Lithuanian national TV, two lessons for TV project "The school of creativity" (Lithuanian National Television); member of LATGA,; member of AGATA, .
  • M. Bloznelis. Invited speaker at 8th Nordic-Baltic Biometrics Conference, Helsinki, 7–10 June 2021. Lecture: On subgraph counts in sparse complex networks.


DEPARTMENT OF SOFTWARE ENGINEERING

Didlaukio 47, LT-08303 Vilnius
Tel. 219 5040
E-mail:
Head – Dr Karolis Petrauskas

STAFF

Professor: Dr R. Baronas.
Professors of practice: Dr G.Alzbutas (part-time), Dr V. Ašeris (part-time), Dr E. Pakalnickas (part-time), Dr E. Pakalnickienė (part-time), Dr D. Sauliūnas (part-time), Dr G. Slivinskas (part-time).
Associate professors: Dr V. Čyras, Dr S. Dapkūnas, Dr K. Lapin, Dr K. Petrauskas (part-time), Dr S. Ragaišis.
Associate professors of practice: V. Jusevičius (part-time), V. Pozdniakov (part-time).
Assistant professors: Dr Ž. Ledas (part-time), Dr S. Peldžius (part-time), Dr L. Petkevičius (part-time), Dr T. Plankis, Dr V. Valaitis.
Teaching assistant: B. Dapkūnas (part-time).
Lecturers: A. Gimbutas (part-time), S. Girdzijauskaite (part-time), A. Jankus (part-time), D. Kimutis (part-time), P. Marcinkevičius (part-time), L. Sakson (part-time), J. Ragaišis (part-time), G. Rimša (part-time), V. Sabalys (part-time), V. Savin (part-time), Dr. R.Savukynas (part-time), T. Smagurauskas (part-time), A. Šimkus (part-time), K. Uosis (part-time), Dr. A. Vaitkevičienė (part-time), J. Žagūnas (part-time), R. Žagūnienė (part-time).
Doctoral student: B. Dapkūnas.

RESEARCH INTERESTS

Software process modelling, assessment and improvement
Learning process assessment and improvement
Teaching software engineering
User experience quality models
Decision support in time-critical systems
Legal informatics and artificial intelligence
Modelling and computational calculations
Computational modelling of chemical and biological processes and systems
Formal methods in software engineering for distributed systems
Deep learning models in computer vision
Deep learning application for medical image analysis

RESEARCH PROJECTS CARRIED OUT IN 2021

Projects Supported by University Budget

Modelling of Computerized Systems and their Development Process. Assoc. Prof. K. Petrauskas. 2019–2022.

The monograph “Mathematical modeling of biosensors. Second edition” covers the mathematical aspects and presents unique digital modeling methods for a wide range of biosensors. It is great compendium of biosensor modelling and development for researchers in both chemistry and mathematics.
Novel Lithuanian language model was created and applied for predicting occupancy based on finished study program description, using transformer neural networks.
Novel framework to combine the learnable modules to follow trajectories from data to graph-based topology for autonomous navigation was developed.
The anomalies identification method for identifying gearbox faults in gear-box signals were developed.
The issues were identified and recommendations were proposed, from the investigation of Child protection service (CPS) based on client/information system (IS) interactions.
Formalization and visualization of legal was investigated.
Formal verification of round based randomized consensus algorithms was investigated.
DevOps and Agile processes modelled, investigated and their behavior assessed.
Correctness of a spacegroup builder algorithm for crystallography problems with optimized and non-optimized operation was elaborated.

Main publications:

Baronas, R., Ivanauskas, F., Kulys, J. Mathematical modeling of biosensors. Second edition. Cham: Springer International Publishing. 2021, 473 p. DOI: 10.1007/978-3-030-65505-1.

Baronas, R., Kulys, J., Petkevičius, L. Modeling carbohydrates oxidation by oxygen catalyzed by bienzyme glucose dehydrogenase/laccase system immobilized into microreactor with carbon nanotubes. Journal of Mathematical Chemistry. 2021, 59: 168–185. DOI: 10.1007/s10910-020-01187-2.

Daniušis, P., Valatka, L., Juneja, S., Petkevičius, L. Topological navigation graph framework. Autonomous Robots. 2021, 45: 633–646. DOI: 10.1007/s10514-021-09980-x.

MAIN R&D&I (RESEARCH, DEVELOPMENT AND INNOVATION) PARTNERS

University of Vienna (Austria)
National Cancer Institute (Lithuania)
Center for Physical Sciences and Technology (Lithuania)
National Cancer Institute (Lithuania)
Nature Research Centre (Lithuania)

MOST IMPORTANT PARTICIPATION CASES OF RESEARCHERS IN WORKING GROUPS OR COMMISSIONS SET UP BY STATE AUTHORITIES, STATE AND MUNICIPAL INSTITUTIONS, ORGANISATIONS, BUSINESS ENTITIES

  • Dr Linas Petkevičius: participant in the activities of the Lithuanian Standards Board, sct. 42.

OTHER RESEARCH ACTIVITIES

Prof. R. Baronas –

Assoc. Prof. V. Čyras –

Assoc. Prof. K. Lapin –

  • scientific collaboration with the Systems Research Institute of the Polish Academy of Sciences, Prof. Ignacy Kaliszewski’s scientific group.

Assoc. Prof. S. Ragaišis –

Dr Linas Petkevičius –

  • editorial board member of the Nonlinear Analysis: Modelling and Control Journal, http://www.mii.lt/NA;
  • board member of Artificial Intelligence Association of Lithuania (AIAL);
  • member of Institute of Electrical and Electronics Engineers (IEEE);
  • member of Lithuanian Computer Society (LIKS);
  • expert representative of the Lithuanian Standards Board.

MOST IMPORTANT RESEARCH DISSEMINATION ACTIVITIES

  • Dr Vytautas Ašeris: https://www.15min.lt/video/vytautas-aseris-kodel-mums-visiems-svarbi-verslo-ir-mokslu-jungtis-205874.
  • Dr Linas Petkevičius: Publication “Analysis of Natural Language: From Sorting Text Data to Generating Fake Texts”, VU Spectrum, (34), 30/09/2021; Interview. LRT classic, Homo cultus. Turns and perspectives. How modern technology works and transforms the world of us all, 16/09/2021; Interview. LRT, Classic, Department of Space, Realistic Artificial Voice, April 2, 2021; Interview. 15min, IT +: DeepFake visual fakes are horrible - we resurrected Duke Vytautas the Great from the graves, 04/05/2021.


CYBERSECURITY LABORATORY

Didlaukio 47, LT-08303 Vilnius
Tel. 219 5002
E-mail: ,
Head – Assoc. Prof. Dr Linas Bukauskas

STAFF

Associate professors: Dr A. Brilingaitė, Dr L. Bukauskas, Dr K. Lapin.
Senior researchers: Dr L. Ambrozaitytė, Dr I. Domarkienė, Dr D. Lepaitė.
Research assistant: A. Jurevičienė.
Lecturers: V. Krinickij, E. Kutka.
Laboratory assistants: M. Gaubas (part-time), A. Jakubonytė.
Internships: M. Ringytė (USA).
Visiting professors: Dr Stefan Sutterlin (Norway) and Dr Ricardo Gregorio Lugo (Norway), Dr Karen Parish (Norway), Dr Ginta Majore (Latvia), Dr Rūta Pirta-Dreimane (Latvia).

RESEARCH INTERESTS

Computer networks
Cloud and parallel computing, virtualization
Cyber security
Digital forensics
Training environments for cybersecurity
Education in computer science and cybersecurity

RESEARCH PROJECTS CARRIED OUT IN 2021

Projects Supported by University Budget

Research on Detection of Premeditated Security Vulnerabilities in Mobile Applications and New Efficient TKHC-Based Image Sharing Scheme over Unsecured Channel Was Conducted. 2019–2023.

Rising numbers and sophistication of security threats in the digital domain cause an increase in the demand for skilled cybersecurity professionals. In response, cybersecurity exercises, and in particular - cyber defence exercises (CDX) are becoming ever more popular. They provide a training platform to simulate real-life situations. CDX are significant events involving months of preparation, and previous studies show a lack of objective evidence of their relevance regarding the learning impact. Skills of exercise participants are usually different and vary from tech-savvy to beginners. Also, trainees are diverse when considering their background, current work profile (position and institution), and experience. Assessment of their competencies is essential to ensure quality in training. The project aims were to investigate information sharing techniques during CDX events and cryptographic methods for efficient video image sharing.

Main publications:

Domarkienė, I., Ambrozaitytė, L., Bukauskas, L., Rančelis, T., Sütterlin, S., Knox, B. J., Maennel, K., Maennel, O., Parish, K., Lugo, R. G. and Brilingaitė, A. CyberGenomics: Application of Behavioral Genetics in Cybersecurity. Behavioral Sciences. 2021, 11(11): 152. https://doi.org/10.3390/bs11110152.

Hodeish, M. E., Bukauskas, L. and Humbe, V. T. A new efficient TKHC-based image sharing scheme over unsecured channel. Journal of King Saud University: Computer and Information Sciences. 2019, 25. DOI: 10.1016/j.jksuci.2019.08.004, (in press).

Research Projects

Development of the National Cybersecurity Competence Map (Nacionalinio kibernetinio saugumo kompetencijų žemėlapio kūrimas) (No. P-REP-21-2, 2020). L. Bukauskas, A. Brilingaitė, D. Lepaitė. 2021.

This project aims to prepare the first Lithuanian cyber competence map together with recommendations on how to attract specialists to the Cybersecurity (CS) sector and how to advance their competencies. During the project, we will explore the demand for CS specialists in Lithuania and the world, survey the opinions of CS professionals, management and specialists from private and public sector organizations, including national defence sector. Also, we will determine the career path of the specialists, analyze job offers, distinguish work roles, and gather findings and recommendations from scientific research papers and similar reports of other countries. The results of the project will include a publicly available database of collected data, expert findings of the research and recommendations for stakeholders, and a submitted scientific article to promote the results.

Baltic Research Programme EEA Grant. ADVANCES: Advancing Human Performance in Cybersecurity (No S-BMT-21-6 (LT08-2-LMT-K-01-051). Dr A. Brilingaitė (proj. leader), L. Bukauskas. 2021–2023.

This project focuses on human performance improvement. Human error is the leading cause of data and security breaches. It has been proven in many cyber crises that the strength of the cyber resiliency capability is highly related to the resiliency of a human at play and coordinated actions of relevant actors. Cybersecurity strategies of the three Baltic countries unanimously emphasize the lack of cybersecurity specialists and the need to fill this gap by strengthening knowledge exchange and education programs. A coherent interdisciplinary approach that encompasses technology and human aspects is crucial to create new innovative training methods and environments in order to overcome the rising security problems. This project aims to establish a new interdisciplinary collaborative network among leading Baltic, Liechtenstein, and Norwegian research institutions. The network has been supported by national/international organizations and a private sector company. The recent development of crisis (such as COVID-19) handling shows the impact of digital technologies where human behaviour and comprehensive understanding of cybersecurity surpasses infrastructural technological solutions. Most economic sectors in Europe depend increasingly on protection against cybercrime. Moreover, IT security workers should be prepared for the future cyber crisis that may have a devastating impact on the national economy and security. The close and continuous cross-border cooperation with the national/international institutions and the private company ensures that the research outcomes will help fulfil these objectives. The project will further increase the sustainability of the outcomes by implementing long-term educational training schemes, ongoing student-/staff mobility between academic partners, involving students in private enterprises, and the integration of private enterprises into educational development.

Main publications:

Domarkienė, I., Ambrozaitytė, L., Bukauskas, L., Rančelis, T., Sütterlin, S., Knox, B. J., Maennel, K., Maennel, O., Parish, K., Lugo, R. G. and Brilingaitė, A. CyberGenomics: Application of Behavioral Genetics in Cybersecurity. Behavioral Sciences. 2021, 11(11): 152. https://doi.org/10.3390/bs11110152.

Ambrozaitytė, L., Brilingaitė, A., Bukauskas, L., Domarkienė, I., Rančelis, T. Human Characteristics and Genomic Factors as Behavioural Aspects for Cybersecurity. In: Schmorrow D.D., Fidopiastis C.M. (Eds.) Augmented Cognition. HCII 2021. Lecture Notes in Computer Science, vol 12776. Springer, Cham. https://doi.org/10.1007/978-3-030-78114-9_23.

Jurevičienė, A., Brilingaitė, A., Bukauskas, L. Digital Human in Cybersecurity Risk Assessment. In: Schmorrow D. D., Fidopiastis C. M. (Eds.) Augmented Cognition. HCII 2021. Lecture Notes in Computer Science, vol 12776. Springer, Cham. https://doi.org/10.1007/978-3-030-78114-9_29.

MAIN RESEARCH ACHIEVEMENTS IN 2021

Overcoming Information Sharing Challenges in Cyber Defence Exercises (final stage of Journal review), Journal of Security Oxford University Press.
Age and Gender Impact on Password Hygiene (submitted).
CyberGenomics: Approaches for Personalized Risk Assessment.
Financial Fraud Pattern Mining on Large Scale Dynamic Blockchain Transactions.
Algorithm for Incident Alignment of Asynchronous Processes.

MAIN R&D&I (RESEARCH, DEVELOPMENT AND INNOVATION) PARTNERS

Armed forces of Lithuania (Lithuania)
Aalborg University (Denmark)
General Jonas Žemaitis Military Academy of Lithuania (Lithuania)
Norwegian University of Technical and Natural Sciences – NTNU (Norway)
Liechtenstein University (Liechtenstein)
Østfold University College (Norway)
University of Padua (Italy)
Riga Technical University (Latvia)
Strategeens, JSC (Lithuania)
Tallinn Technical University (Estonia)
Tartu university (Estonia)
Vidzeme University of Applied Sciences (Latvia)

OTHER RESEARCH ACTIVITIES

Assoc. Prof. A. Brilingaitė –

Assoc. Prof. L. Bukauskas –

  • board member of Technical Committee No. 86 for Digital geographic information at the Department of Standardization;
  • steering committee chair, International Conference on Advances in Computer Vision and Artificial Intelligence Technologies (ACVAIT2022);
  • guest associate editor of the Journal of Frontiers in Education special issue The Human Factor in Cyber Security Education;
  • member of IEEE organization.

MOST IMPORTANT PARTICIPATION CASES OF RESEARCHERS IN WORKING GROUPS OR COMMISSIONS SET UP BY STATE AUTHORITIES, STATE AND MUNICIPAL INSTITUTIONS, ORGANISATIONS, BUSINESS ENTITIES

  • Assoc. Prof. L. Bukauskas: member of the National Cyber Security Board under Ministry of Defence of the Republic of Lithuania; expert/Reviewer of research projects and proposals, European Commission; expert/monitor of executed research projects, European Commission; Vice-President of non-profit organisation Geens.com vzw, Belgium.

MOST IMPORTANT RESEARCH DISSEMINATION ACTIVITIES

INSTITUTE OF MATHEMATICS

Naugarduko 24, LT–03225 Vilnius
Tel.: 219 3085
E-mail:
Director – Prof. Dr Jonas Šiaulys
http://mif.vu.lt/lt3/en/about/structure/institute-of-mathematics

STAFF

Professors: Dr P. Drungilas, Dr R. Garunkštis (part-time), Dr Habil. V. Mackevičius, Dr Habil. E. Manstavičius (emeritus), Dr Habil. V. Paulauskas (emeritus), Dr G. Stepanauskas, Dr J. Šiaulys.
Professors of practice: Dr G. Bakštys, Dr A. Linartas.
Associate professors: Dr A. Balčiūnas, Dr A. Elijio, Dr E. Gaigalas, Dr A. Grigutis, Dr R. Kašuba, Dr M. Manstavičius, Dr E. Mazėtis.
Research professors: Dr R. Garunkštis (part-time), Dr Habil. A. Dubickas, Dr Habil. A. Laurinčikas.
Senior researcher: Dr J. Jankauskas (part-time).
Assistant professors: Dr J. Damarackas, Dr D. Dzindzalieta, Dr E. Globienė, Dr E. Jaunė, Dr E. Karikovas, Dr A. Lenkšas, Dr A. Novikas, Dr A. Skučaitė, Dr V. Stepas, Dr R. Šimėnas, Dr R. Tamošiūnas (part-time), Dr A. Zinevičius.
Teaching assistants: G. Bagdonas, E. Gutauskaitė, V. Jurgelevičius, G. Liaudanskaitė, L. Maciulevičius.
Lecturers: Š. Dirmeikis, Dr. A. Kačėnas (part-time), I. Mikulėnas (part-time).
Affiliate associate professors: Dr R. Kudžma, Dr G. Misevičius.
Doctoral students: G. Bagdonas, G. Gangopadhyay, E. Gutauskaitė, R. Gylys, M. Jasas, G. Junevičius, V. Jurgelevičius, J. Karasevičienė, L. Klebonas, G. Lileika, V. Lukšienė, L. Kaziulytė, T. Kuras, M. Montessinos, L. Maciulevičius, G. Mongirdaitė, S. Paukštys, R. Puišys, J. Sprindys, A. Šmergelytė, P. Tarasov, M. Tekorė, G. Vadeikis, A. Vaiginytė, G. Ziezys, B. Žemaitienė.

DEPARTMENTS OF INSTITUTE
Department of Mathematical Analysis
Department of Probability Theory and Number Theory
Group of Analytic Number Theory
The Center for Mathematics Education

RESEARCH AREAS

Fundamental mathematics: number theory, probability theory and stochastic analysis, risk theory
Applied mathematics: methods of mathematical statistics, mathematical modelling, finance and insurance mathematics, modern elementary mathematics and didactics

MAIN CONFERENCES ORGANIZED IN 2021

Conference in Probability and Number Theory dedicated to 60th anniversary of the Department of Probability Theory and Number Theory of Vilnius University. Palanga, 14–19 September 2021.

MAIN SCIENTIFIC ACHIEVEMENTS IN 2021

The asymptotic lower and upper bounds are obtained for the tails of higher-order moments of sums with heavy-tailed increments.
The limit behavior of sums of linear processes is established in the case where innovations and filter of a linear process are tapered, and the parameters of tapering depend on the number of summands.
It was shown that Pillai’s equation in polynomials has at most one solution except for the three explicitly described cases when it has exactly two solutions.
Joint approximation of analytic function by shifts of periodic zeta-functions twisted by the sequence of imaginary points of non-trivial zeros of the Riemann zeta-function is obtained.
Linear statistics defined on random permutations or on polynomials over a finite field were explored. Optimal lower and upper bounds for the variance were obtained.

BEST REPORTS DELIVERED AT CONFERENCES ABROAD

  • J. Šiaulys. Tails of the moments for sums with dominatedly varying random summands. Modern Stochastics: Theory and Applications V. Kyiv, 1–4 June 2021.
  • J. Šiaulys. R. Leipus. On closure properties of convolution equivalent distributions, Modern Stochastics: Theory and Applications V. Kyiv, 1–4 June 2021.
  • A. Dubickas. Transcendency of some constants related to integer sequences of polynomial iterations, Diophantine Analysis and Related Topics, Moscow Workshop on Combinatorics and Number Theory (via Zoom), 31 May–05 June 2021.
  • A. Dubickas. On polynomial Sidon sequences, Nineteenth Annual Workshop on Combinatorial and Additive Number Theory, CUNY Graduate Center (via Zoom), New York, 24–28 May 2021.
  • M. Manstavičius, E. Gutauskaitė. Multivariate concordance measures revisited (Diversity of bivariate concordance measures), CFE-CMStatistics 2021 Conference, London, 18–21 December 2021.

MOST IMPORTANT NATIONAL AND INTERNATIONAL AWARDS RECEIVED FOR R&D ACTIVITIES

  • Vygantas Paulauskas, Professor Emeritus, awarded The Cross of the Officer of the Order of the Grand Duke of Lithuania Gediminas.

MOST IMPORTANT PARTICIPATION CASES OF RESEARCHERS IN WORKING GROUPS OR COMMISSIONS SET UP BY STATE AUTHORITIES, STATE AND MUNICIPAL INSTITUTIONS, ORGANISATIONS, BUSINESS ENTITIES

  • Dr A. Skučaitė is co-vice chairperson of Social Security Committee and member of Health Section Board. Doctoral student R. Gylys is member of Insurance Accounting Committee, International Actuarial Association, http://www.aktuaries.org/.
  • Doctoral student R. Gylys: member of the Institute and Faculty of Actuaries, https://www.actuaries.org.uk.
  • Prof. G. Bakštys, Dr A. Skučaitė and doctoral student R. Gylys: members of the Lithuanian Actuarial Society, http://www.aktuarai.lt.
  • Dr M. Manstavičius – president, Prof. V. Paulauskas - member of the Lithuanian Statistical Society, http://www.statistikusajunga.lt.
  • R. Norvaiša is a representative of Lithuania, OECD working group Education 2030.

CONSULTATIONS PROVIDED BY THE UNIT TO THE PUBLIC OR ECONOMIC ENTITIES

  • A.Skučaitė: consultation to The State Social Insurance Fund Board under the Ministry of Social Security and Labour.

MOST IMPORTANT RESEARCH DISSEMINATION ACTIVITIES

  • 10th Meeting of Lithuanian Young Mathematicians, http://lmd.mif.vu.lt: Prof. P. Drungilas, Prof. J Šiaulys, Dr M. Manstavičius, Dr A. Grigutis, doctoral students J. Sprindys, G. Bagdonas.
  • Podcast “Talk in laboratory” about mathematics at school, in real life and what to do that more students would pass exams: N. Mačiulis (Swedbank) ir R. Norvaiša, 29 March 2021.
  • K. Tamelytė. Interview with mathematician R. Norvaiša: ”Abstract thinking can be learned in primary school”, Bernardinai.lt, 4 February.
  • Radio show ”Dešimt balų”: Ar naujų mokyklinių programų rengėjai išgirdo tarptautinių ekspertų rekomendacijas, kai derėtų keisti programų turinį? 20 April 2021.
  • Interview with mathematician R. Norvaiša and philosopher D. Harbdankaite. Bernardinai.lt 9 December 2021.


DEPARTMENT OF MATHEMATICAL ANALYSIS

Naugarduko 24, LT-03225 Vilnius
Tel.: 219 3085
E-mail:
Head – Prof. Dr Jonas Šiaulys

STAFF

Professors: Dr Habil. V. Mackevičius, Dr Habil. V. Paulauskas (Emeritus), Dr G. Stepanauskas, Dr J. Šiaulys.
Professors of practice: Dr. G. Bakštys, Dr. A. Linartas.
Associate professor: Dr M. Manstavičius.
Teaching assistants: Dr J. Damarackas, Dr D. Dzindzalieta, Dr E. Globienė, Dr R. Gylys, Dr E. Jaunė, Dr. A Lenkšas, Dr A. Skučaitė.
Research assistants: E. Gutauskaitė, J. Karasevičienė, G. Liaudanskaitė.
Lecturers: Š. Dirmeikis, I. Mikulėnas (part-time).
Affiliated fellows: A. E. Plikusas.
Doctoral students: G. Bagdonas, R. Gylys, E. Gutauskaitė, G. Mongirdaitė, V. Jurgelevičius, J. Karasevičienė, T. Kuras, G. Lileika, S. Paukštys, R. Puišys, R. Prigodin, J. Sprindys, B. Žemaitienė.

RESEARCH INTERESTS

Mathematical analysis
Heavy-tailed distributions
Probability limit theorems
Stochastic analysis
Stochastic numerics
Actuarial mathematics
Financial mathematics
Risk theory

RESEARCH PROJECTS CARRIED OUT IN 2021

Projects Supported by University Budget

Studies of Random Processes and Fields and Their Applications in Financial and Actuarial Mathematics. Prof. J. Šiaulys. 2016–2021.

Second-order weak approximations of CKLS and CEV processes by discrete random variables are constructed and investigated.

The asymptotic lower and upper bounds are obtained for the tails of higher-order moments of sums with heavy-tailed increments. The bounds are derived for the variables having dominatedly varying or consistently varying distributions. The derived results are applied to get asymptotic estimations for the Haezendock-Goovaerts risk measure.

Limit behaviour of sums of linear processes were investigated in the case where innovations and filter of a linear process are tapered, and the parameters of tapering depend on the number of summands.

Constructions of bivariate concordance measures for continuous random variables were investigated. Asymptotical behaviour of classical number theoretical functions was studied.

Actuarial analysis is presented an survival among breast cancer patients in Lithuania.

Main publications:

Lileika, G., Mackevičius, V. Second-order weak approximations of CKLS and CEV processes by discrete random variables. Mathematics. 2021, 9: 1337.

Sprindys, J., Šiaulys, J. Asymptotic formulas for the left truncated moments of sumd with consistently varying distributed increments, Nonlinear Analysis: Modeling and Control. 2021, 26(6): 1200–1212.

Leipus, R., Paukštys, S., Šiaulys, J. Tails of higher-order moments of sums with heavy-tailed increments and application to the Haezendock-Goov aerts risk measure. Statistics and Probability Letters. 2021, 170: 108998.

MAIN R&D&I (RESEARCH, DEVELOPMENT AND INNOVATION) PARTNERS

Taras Shevchenko National University of Kyiv (Ukraine)
Mälardalen University (Sweden)
University of Siegen (Germany)
Tartu University (Estonia)
University of Bonn (Germany)
Soochow University (China)
Nanjing Audit University (China)
Polish Academy of Science, Institute of Mathematics (Poland)

OTHER RESEARCH ACTIVITIES

Prof. V. Mackevičius –

Prof. V. Paulauskas (Emeritus) –

Prof. J. Šiaulys –

  • editorial board member of the Lithuanian Mathematical Journal;
  • editorial board member of the Modern Stochastics: Theory and Applications;
  • editorial board member of the Nonlinear Analysis: Modelling and Control;
  • member of the Lithuanian Mathematical Society, http://www.mif.vu.lt/lmd/index_en.html.

Prof. G. Stepanauskas –

Prof. G. Bakštys –

Assoc. Prof. M. Manstavičius –

Dr A. Skučaitė –

Dr R. Gylys –


DEPARTMENT OF PROBABILITY THEORY AND NUMBER THEORY

Naugarduko 24, LT–03225 Vilnius
Tel.: 219 3059
E-mail:
Head – Prof. Dr Habil. Artūras Dubickas

STAFF

Professors: Dr P. Drungilas, Dr Habil. A. Laurinčikas (Emeritus), Dr Habil. E. Manstavičius (Emeritus).
Associate professors: Dr A.Balčiūnas, Dr J. Jankauskas (part-time), Dr E. Mazėtis, Dr A. Novikas.
Research professor: Dr Habil. A. Dubickas.
Senior researcher: Dr J. Jankauskas (part-time).
Teaching assistants: Dr V. Stepas, Dr A. Zinevičius.
Research assistant: L. Maciulevičius.
Lecturer: Dr A. Kačėnas (part-time).
Affiliated fellows: Dr R. Kašuba, Dr G. Misevičius.
Doctoral students: G. Gangopadhyay, M. Jasas, G. Junevičius, A. Karbonskis, L. Klebonas, V. Lukšienė, M. Montessinos, L. Maciulevičius, M. Savitienė, A. Šmergelytė, G. Vadeikis, A. Vaiginytė, P. Virbalas, G. Ziezys.

RESEARCH INTERESTS

Algebraic numbers and polynomials
Analytic number theory
Combinatorics
Probabilistic number theory

RESEARCH PROJECTS CARRIED OUT IN 2020

Projects Supported by University Budget

Problems of Number Theory and Investigation of Roots of Polynomials. Prof. A Drungilas, Prof. A. Garunkštis, Prof. A. Dubickas, Prof. A. Laurinčikas, Prof. E. Manstavičius. 2019–2023.

It was shown that Pillai’s equation in polynomials has at most one solution except for the three explicitly described cases when it has exactly two solutions. We also proved a theorem about group of units of some specially constructed cubic extensions which implies that the corresponding Oeljeklaus–Toma manifold admits a pluriclosed metric.
We showed that the existence of second moment of the Selberg zeta-function is related to the properties of certain Beurling natural numbers. Here the behaviour of the counting function and the distribution of minimal gaps between these Beurling natural numbers are important. We also obtained unconditional upper bounds for these moments.
Joint approximation of analytic function by shifts of periodic zeta-functions twisted by the sequence of imaginary points of non-trivial zeros of the Riemann zeta-function is obtained.
Linear statistics defined on random permutations or on polynomials over a finite field were explored. Optimal lower and upper bounds for the variance were obtained.

Main publications:

Dubickas, A. Pillai’s equation in polynomials. Mediterranean Journal of Mathematics. 2021, 18(2): 63.

Drungilas, P., Garunkštis, R., Novikas, A. On Second Moment of Selberg Zeta-Function for sigma=1, Results in Mathematics. 2021, 76: 184.

Laurinčikas, A., Šiaučiūnas, D., Tekorė, M. Joint universality of periodic zeta-functions with multiplicative coefficients. II. Nonlinear Analysis Modelling and Control. 2021, 26(3): 550–564.

International Research Projects

European Social Fund. Approximations by Zeta-Functions and Algebraic Numbers (No. 09.3.3-LMT-K-712-01-0037). Prof. Dr Habil. A. Laurinčikas. 2017–2021.

Using some translations of Chebyshev polynomials, we gave some sharp inequalities between height and deviation of polynomials. Also, given an algebraic number of degree d, we proved some estimates (in terms of d) on the number of positive integers for which the power of an algebraic number to that integer is an algebraic number of degree strictly smaller than d.
Let Z(s) be the Selberg zeta-function associated to a compact Riemann surface. We considered decompositions Z(s)=f(h(s)), where f and h are meromorphic functions, and showed that such decompositions can only be trivial. Moreover, an absolutely convergent Dirichlet series whose shifts approximate a wide class of analytic functions is constructed. We proved that this series is close in the mean to the Riemann zeta-function.

Main publications:

Dubickas, A. Inequalities between height and deviation of polynomials. Open Mathematics. 2021, 19(2021): 540–¬550.

Garunkštis, R. Selberg zeta-function associated to compact Riemann surface is prime. Revista de la Unión Matemática Argentina. 2021, 62: 213–218.

Laurinčikas, A. Approximation of analytic functions by an absolutely convergent Dirichlet series. Arch. Math. 2021, 117(2021): 53–63.

European Social Fund. An Investigation of the Selberg Zeta Function (No. 09.3.3-LMTK-712-19- 0030). Prof. Dr Habil. A. Dubickas (advisor), R. Šimėnas (postdoctoral student). 2020–2022.

Prof. Lejla Smajlović at University of Sarajevo, Bosnia and Herzegovina was visited, worked on the topic of automorphic forms there. Currently writing an article on the McKean formula for the Selberg zeta function associated with Hilbert modular surfaces. Having biweekly consultations with Prof. Lejla Smajlović and Prof. Jay Jorgenson.

MAIN R&D&I (RESEARCH, DEVELOPMENT AND INNOVATION) PARTNERS

Moscow University (Russia)
Nagoya University (Japan)
Würzburg University (Germany)
Oklahoma State university (USA)
Montanuniversität Leoben (Austria)
South China Normal University (Guangzhou, China)

OTHER RESEARCH ACTIVITIES

Prof. A. Dubickas –

Prof. A. Laurinčikas (Emeritus) –

Prof. E. Manstavičius (Emeritus) –


ANALYTIC NUMBER THEORY GROUP

Naugarduko 24, LT–03225 Vilnius
Tel. 219 3081
E-mail:
Head – Prof. Dr Ramūnas Garunkštis

STAFF

Professors: Dr R. Garunkštis (part-time), Dr R. Macaitienė (part-time, Šiauliai Academy), Dr D. Šiaučiūnas (part-time, ŠA).
Research professors: Dr R. Garunkštis (part-time) Dr. R. Macaitienė (part-time, ŠA).
Associate professors: Dr Virginija Garbaliauskienė (part-time, ŠA), Dr A. Grigutis, Dr R. Šimėnas.
Senior researchers: Dr. Virginija Garbaliauskienė (part-time, ŠA), Dr. Darius Šiaučiūnas (part-time, ŠA).
Assistant professors: Dr E. Karikovas, Dr R. Tamošiūnas (part-time).
PhD student: T. Kondratavičius

RESEARCH INTERESTS

Zeta functions
Universality theorems
Multiplicative structures
Risk models

OTHER RESEARCH ACTIVITIES

Prof. R. Garunkštis –

  • member of the program committee of the 62nd conference of the Lithuanian Mathematical Society;
  • editor of the Lithuanian Mathematical Journal.

Assoc. Prof. V. Garbaliauskienė –

Prof. R. Macaitienė –

Prof. D. Šiaučiūnas –


THE CENTER FOR MATHEMATICS EDUCATION

Naugarduko 24, LT-03225 Vilnius
Tel. 219 3075
E-mail:
Head – Prof. Dr Habil. Rimas Norvaiša

STAFF

Professors: Dr Habil. A Dubickas, Dr P. Drungilas, Dr Habil. R. Norvaiša.
Associate professors: Dr A. Elijio, Dr E. Mazėtis, Dr A. Novikas.
Affiliated fellows: Dr R. Kašuba, Dr R. Kudžma.
Doctoral students: V. Miežys, I. Kilienė

RESEARCH INTERESTS

Research of pedagogical content knowledge of teachers of mathematics and content analysis of elementary mathematics
Research of mathematical problems and mathematical models
Development of working methods with children gifted in mathematics

RESEARCH PROJECTS CARRIED OUT IN 2021

Projects Supported by University Budget

Mathematics Education Research. Prof. Dr Habil. R. Norvaiša. 2020–2024.

Mathematics education philosophy and politics. Establishment of methodical material of elementary mathematics for teachers. Research and creation of word problems motivating mathematical reasoning. Making dictionary of concepts of school mathematics.
We prepared the problems for Lithuanian mathematical olympiad, team olympiad and
a selection test for Baltic Way olympiad. In 2021, the members of the center were team
leaders for Lithuanian teams participating at the IMO (International Mathematical Olympiad,
held online), MEMO (Middle European Mathematical Olympiad, which was a hybrid event),
and the team olympiad Baltic Way, which was a live event in Iceland.

Main publications:

Kašuba, R., Mazėtis, E. Can we pose problems that are attractive, yet accessible to many. Engaging young students in mathematics trough competitions, world perspectives and practices. World Scientific. 2020, 1: 87–107.

Dubickas, A. Problems and solutions of the Lithuanian Mathematical Olympiad of the year 2021. 2021, 9 p. (in Lithuanian), https://klevas.mif.vu.lt/~dubickas/files/dvifai/2021LMO.pdf.

Drungilas, P., Dubickas, A. Mathematical Competition for Students of the Department of Mathematics and Informatics of Vilnius University. Problems and Solutions. 2021, 4 p.
https://klevas.mif.vu.lt/~dubickas/files/dvifai/2021sprend.pdf.

Projects supported by the National Agency for Education

Development of the System to Supervise Students’ Achievements and Creation of Instruments to Establish Accumulative Assessments (No. 09.2.1-ESFA-V-706-02-0001). Participants V. Miežys, R. Norvaiša.

Creation and Implementation of Digital Educational Content (No. 09.2.1-ESFA-V-726-03-0001). Participants E. Mazėtis, R. Norvaiša.

Projects supported by the Research Council of Lithuania

The Development of Mathematical Reasoning in School (No. P-DNR-21-9). Head: R. Norvaiša, researchers: I. Kilienė, V. Miežys. 21 April 2021–31 December 2021.

MAIN R&D&I (RESEARCH, DEVELOPMENT AND INNOVATION) PARTNERS

Tartu University (Estonia)

OTHER RESEARCH ACTIVITIES

Affiliated fellow Dr R. Kašuba –

  • board member of Lithuanian Mathematical Society, http://www.mif.vu.lt/lmd/;
  • board member of Lithuanian Kangaroo Committee, http://www.kengura.lt;
  • editorial board member of the MCG Mathematical Creativity and mathematical Giftedness newsletter, Editor of Problem corner, www.igmcg.org/newsletter.html;
  • board member of the Lithuanian School of Young Mathematicians, http://www.mif.vu.lt/ljmm/.

Assoc. Prof. E. Mazėtis –

Prof. R. Norvaiša –

Assoc. Prof. Dr A. Novikas –

Assoc. Prof. A. Elijio –

 

INSTITUTE OF APPLIED MATHEMATICS

Naugarduko 24, LT-03225 Vilnius
Tel. 219 5043
E-mail: ,
www http://www.mif.vu.lt
https://mif.vu.lt/lt3/en/about/structure/institute-of-applied-mathematics
Director – Prof. Dr Habil. Remigijus Leipus

STAFF

Professors: Dr A. Ambrazevičius, Dr Habil. V. Bagdonavičius, Dr Habil. V. Čekanavičius, Dr P. Katauskis, Dr Habil. R. Leipus, Dr Habil. R. Norvaiša (part-time), Dr Habil. K. Pileckas, Dr Habil. A. Račkauskas, Dr Habil. M. Radavičius, Dr Habil. D. Surgailis (emeritus), Dr O. Štikonienė.
Researchers: Dr K. Karčiauskas, Dr R. Norvaiša (part-time), Dr Habil. K. Pileckas, Dr Habil. A. Račkauskas (part-time), Dr A. Štikonas, Dr R. Vidunas (part-time).
Associate professors: Dr K. Kaulakytė, Dr V. Kazakevičius, Dr A. Kregždė, Dr R. Levulienė, Dr J. Markevičiūtė (part-time), Dr G. Murauskas, Dr G. Puriuškis, Dr V. Skorniakov, Dr R. Vidunas (part-time).
Professor of practice: T. Marčiulaitis.
Assistant professors: Dr A. Buteikis, Dr D. Celov, Dr R. Giniūnaitė, Dr E. Karikovas, Dr A. Kavaliauskas, Dr Š. Repšys. Dr J. Venskus (part-time).
Teaching assistants: S. Jokubaitis, R. Juodagalvytė, I. Kilienė, N. Kozulinas, A. Medžiūnas, V. Šumskas.
Lecturers: Dr R. Eidukevičius, V. Maniušis.
Affiliate professor: Dr V. Skakauskas.
Doctoral students: K. Bartkus, A. Birbilas, U. Čižikovienė, T. Danielius, J. Gudan, S. Jokubaitis, R. Juodagalvytė, I. Kilienė, N. Kozulinas, V. Miežys, G. Liaudanskaitė, V. Šumskas, L. Vabalas.

DEPARTMENTS OF INSTITUTE OF APPLIED MATHEMATICS
Department of Differential Equations
Department of Statistical Analysis

RESEARCH AREAS

Fundamental mathematics: number theory, probability theory and stochastic analysis, theory of differential equations, functional analysis
Applied mathematics: methods of mathematical statistics, mathematical modelling, econometrics, time series analysis, insurance mathematics

MAIN CONFERENCES ORGANIZED IN 2021

8th European Congress of Mathematics, Minisymposia “Multiscale Modeling and Methods: Application in Engineering, Biology and Medicine“, 20–26 June 2021(remotely).

International workshop “Mathematical Modeling in Hemodynamics”, 8 December 2021, Saint-Etienne and online.

Fudan International Seminar on Analysis, PDEs, and Fluid mechanics, 2021, online, organized by Fudan University (Shanghai, China, Z Lei, M. Korobkov), Universita degli studi della Campania "Luigi Vanvitelli" (Caserta, Italy, A. Ferone, R. Russo) and Vilnius University (Vilnius, Lithuania, K. Pileckas), https://researchseminars.org/seminar/Cafe_Analysis_and_Fluid.

62nd Conference and Congress of Lithuanian Mathematical Society, 16–17 June 2021, online. Chairman of the programme committee: R. Leipus.

BEST REPORTS DELIVERED AT CONFERENCES ABROAD

  • Štikonienė O. Invited talk “Dynamic modelling of the evolution of SARS-CoV-2 Epidemic in Lithuania.” XVII Baltic conference on intellectual cooperation Mathematics for Society, 28–29 June 2021, Estonian Academy of Sciences, Tallinn.
  • Juodagalvytė R., Panasenko G., Pileckas K. Time periodic Navier-Stokes equations in a thin tube structures motivated by hemodynamic. The 8th European Congress of Mathematics, Portorož, Slovenia, 20–26 June 2021.
  • Kozulinas N., Borodinas S., Kaulakytė K., Panasenko G., Pileckas K. Blood velocity computation inside of a human heart left atrium. The 8th European Congress of Mathematics, Portorož, Slovenia, 20–26 June 2021.
  • Leipus R., Šiaulys J. On closure properties of convolution equivalent distributions. International Conference Modern Stochastics: Theory and Applications V. 1–4 June 2021, Kyiv, Ukraine (online).
  • Šumskas V., Čiegis R., Panasenko G., Pileckas K. ADI scheme for partially dimension reduced heat conduction models. The 8th European Congress of Mathematics, Portorož, Slovenia, 20–26 June 2021.
  • Štikonienė O., Leipus R., Šnaraitė B. Modeling the evolution of COVID-19 in Lithuania. The 8th European Congress of Mathematics, Portorož, Slovenia, 20–26 June 2021.


DEPARTMENT OF DIFFERENTIAL EQUATIONS

Naugarduko 24, LT-03225 Vilnius
Tel. 219 3098
E-mail:
Head - Prof. Dr Habil. Konstantinas Pileckas

STAFF

Professors: Dr A. Ambrazevičius, Dr P. Katauskis, Dr O. Štikonienė, Dr Habil. K. Pileckas (part-time), G. Panasenko (Distinguished professor, part-time).
Researchers: Dr K. Karčiauskas, Dr Habil. K. Pileckas (part-time), Dr A. Štikonas, Dr R. Vidunas (part-time), Dr K. Karčiauskas.
Associate professors: Dr K. Kaulakytė, Dr A. Kregždė, Dr G. Puriuškis, Dr R. Vidunas (part-time).
Assistant professors: Dr R. Giniūnaitė, Dr E. Karikovas, Dr A. Kavaliauskas, Dr Š. Repšys.
Teaching assistants: R. Juodagalvytė, N. Kozulinas, A. Medžiūnas, V. Šumskas.
Affiliate professor: Dr V. Skakauskas.

RESEARCH INTERESTS

Partial differential equations
Mathematical hydrodynamics
Mathematical modelling
Integrodifferential and nonlocal equations
Numerical methods
Computer geometry
Functional analysis

RESEARCH PROJECTS CARRIED OUT IN 2021

Projects Supported by University Budget

Investigation of Solutions to Partial Differential Equations. Prof. Dr Habil. K. Pileckas. 2018–2021.

The stationary and initial boundary value problems for the Navier-Stokes equations were studied in 2D bounded domain with a power cusp singular point on the boundary with a nonzero flow rate. The formal asymptotic expansion of the solution near the singular point was constructed and justified.

Solutions to the obstacle problem for the stationary Navier–Stokes system in a two-dimensional exterior domain were studied. It was proved that the classical Leray solution is always nontrivial. No additional condition (on symmetry or smallness, etc.) was assumed. This is a complete extension of a classical result of C. J. Amick (1988) where nontriviality was proved under symmetry assumption.

Solutions of special initial value problem and find asymptotic formulas of arbitrary order were investigated. The characteristic equation of the boundary value problem for eigenvalues was analyzed and asymptotic formulas of arbitrary order were derived.

The influence of the kinetic and the particle jumping via the catalyst-support interface rate constants on the evolution of the surface reactivity of the supported catalysts was studied numerically using a mean-field model.
A construction that unites the treatment of most popular C^2 bi-cubic and C^1 bi-quadratic splines with the extraordinary points was presented. A minimal polynomial degree for smooth constructions of multi-sided surfaces that guarantees an increasing flexibility in all directions under refinement was established.

Main publications:

Pileckas, K., Račienė, A. Non-stationary Navier-Stokes equations in 2D power cusp domain. I. Construction of the formal asymptotic decomposition. Advances in Nonlinear Analysis. 2021, 10(1): 982–1010.

Pileckas, K., Račienė, A. Non-stationary Navier-Stokes equations in 2D power cusp domain. II. Existence of the solution. Advances in Nonlinear Analysis. 2021,10(1): 1011–1038.

Štikonas, A., Sen, E. Asymptotic analysis of Sturm–Liouville problem with nonlocal integral-type boundary condition. Nonlinear Anal. Model. Control. 2021, 26(5): 969–991.

International Research Projects

European Social Fund. Multiscale Modeling for Viscous Flows in Domains with Complex Geometry (No. 09.3.3-LMT-K-712-01-0012). Prof. K. Pileckas. 2017–2021.
During the period of 2021, the method of asymptotic partial decomposition of a domain proposed and justified for thin domains (rod structures, tube structures consisting of a set of thin cylinders) generates some special interface conditions between the three-dimensional and one-dimensional parts. Tests show good accuracy of the method.

Main publications:

Canon, É., Chardard, F., Panasenko, G., Štikonienė, O. Numerical solution of the viscous flows in a network of thin tubes: equations on the graph. Journal of Computational Physics. 2021, 435(110262): 1–31.

Kaulakytė, K., Kozulinas, N., Pileckas, K. Time-periodic Poiseuille-type solution with minimally regular flow rate. Nonlinear Analysis: Modelling and Control. 2021, 26(5): 947–968.

Panasenko, G., Pileckas, K., Vernescu, B. Steady state non-Newtonian flow with strain rate dependent viscosity in domains with cylindrical outlets to infinity. Nonlinear Analysis: Modelling and Control. 2021, 26(6): 947–968.

European Social Fund. Multiscale Mathematical and Computer Modeling for Flows in Networks: Application to Treatment of Cardiovascular Diseases (No 09.3.3-LMT-K-712-17-0003). Prof. G. Panasenko. 2020−2023.

In 2021, the existence and regularity of a solution of Navier-Stokes equations with boundary conditions for the Bernoulli pressure in thin tube structure were obtained. Also, the existence, uniqueness, and regularity of a solution of the non-Newtonian flow system of equations in thin tube structure were studied. This system of equations with the shear rate dependent viscosity is more adequate for the blood flow modeling than the classical Navier-Stokes equations. The COMSOL compatible geometrical model for the left atrial appendage of the heart based on the computer tomography data is created.

Main publications:

Panasenko, G., Pileckas, K., Vernescu, B. Steady state non-Newtonian flow in thin tube structure: equation on the graph. Algebra i Analiz. 2021, 33(2): 197–214.

Juodagalvytė, R., Panasenko, G., Pileckas, K. Steady-State Navier-Stokes Equations in Thin Tube Structure with the Bernoulli Pressure Inflow Boundary Conditions: Asymptotic Analysis. Mathematics. 2021, 9(19).

Bertoglio, C., Nolte, D., Panasenko, G., Pileckas, K. Reconstruction of the Pressure in the Method of Asymptotic Partial Decomposition for the Flows in Tube Structures. SIAM J. Appl. Math. 2021, 81(5): 2083–2110.

MAIN R&D&I (RESEARCH, DEVELOPMENT AND INNOVATION) PARTNERS

Zürich University, Zurich (Switzerland)
University of Saint Etienne, Saint Etienne (France)
Universit`a degli Studi della Campania “L. Vanvitelli”, Caserta (Italy)
Seconda Università degli Studi di Napoli, Caserta (Italy)
Ferrara of University, Ferrara (Italy)
University of Kassel, Kassel (Germany)
University of Novosibirsk, Novosibirsk (Russia)
Steklov institute of Mathematics, St. Petersburg (Russia)
Fudan University, Shanghai (China)

OTHER RESEARCH ACTIVITIES

Prof. K. Pileckas –

Prof. O. Štikonienė –

Prof. A. Štikonas –

Assoc. Prof. K. Kaulakytė –

  • member of the Lithuanian Mathematical Society.


DEPARTMENT OF STATISTICAL ANALYSIS

Naugarduko 24, LT-03225 Vilnius
Tel. 219 3067
E-mail:
Head – Prof. Dr Habil. Vydas Čekanavičius

STAFF

Professors: Dr Habil. V. Bagdonavičius, Dr Habil. V. Čekanavičius, Dr Habil. R. Leipus, Dr Habil. R. Norvaiša (part-time), Dr Habil. A. Račkauskas (part-time), Dr Habil. M. Radavičius, Dr Habil. D. Surgailis (emeritus).
Researchers: Dr R. Norvaiša (part-time), Dr A. Račkauskas (part-time).
Associate professors: Dr V. Kazakevičius, Dr J. Markevičiūtė (part-time), Dr G. Murauskas, Dr R. Levulienė, Dr V. Skorniakov.
Associate professor of practice: T. Marčiulaitis.
Assistant professors: Dr A. Buteikis, Dr D. Celov, Dr J. Venskus.
Teaching assistants: S. Jokubaitis, I. Kilienė.
Lecturers: Dr R. Eidukevičius, V. Maniušis.

RESEARCH INTERESTS

Time series analysis, financial econometrics
Functional data analysis
Limit theorems in probability and their applications to statistics and econometrics
Bootstrap and other resampling methods in statistics and econometrics
Macroeconometric modelling
High frequency data analysis
Statistical methods in reliability theory and survival analysis and their applications
Asymptotic analysis of distributions of statistics, their approximations and applications
Insurance Mathematics

RESEARCH PROJECTS CARRIED OUT IN 2021

Projects Supported by University Budget

Analysis and Applications of Functions and Stochastic Systems. Prof. A. Račkauskas. 2016–2021.

Rough functions analysis; functional data analysis; approximation of stochastic systems; investigation of long memory processes.
Richter’s type local large deviations were investigated for runs statistics approximating Poisson, negative binomial and binomial distributions. Compound Poisson approximation in total variation was obtained for a special Markov three-state model related to actuarial mathematics.
A bivariate integer-valued autoregressive process of order 1 with copula-joint innovations was proposed. Different parameter estimation methods were analyzed and compared via Monte Carlo simulations. Empirical applications were provided.
Functional data analysis approach is applied to modeling and analyzing daily tax revenues.
Some asymptotic results for p-variation of random walk were obtained and applied to a change point problem.

Main publications:

Jokubaitis, S., Celov, D., Leipus, R. Sparse structures with LASSO through principal components. International Journal of Forecasting. 2021, 37(2): 759–776.

Gudan, J., Račkauskas, A., Suquet, C. Testing mean changes by maximal ratio statistics. Extremes. 2021, 1–42.

Skorniakov, V., Leipus, R., Juzeliūnas, G., Staliūnas, K. Group testing: revisiting the ideas. Nonlinear Analysis: Modelling and Control. 2021, 26(3): 534–549.

National Research Projects

Research Council of Lithuania. Closure Properties of Probability Distributions: Theory and Applications (No S-MIP-20-16). Prof. R. Leipus. 2020–2022.

The complete and systematic characterization of closure properties to operations under consideration for heavy-tailed and related distribution was given. Some applications to risk measures and copulas were considered.

Main publications:

Leipus, R., Paukštys, S., Šiaulys, J. Tails of higher-order moments of sums with heavy-tailed increments and application to the Haezendonck-Goovaerts risk measure. Statistics and Probability Letters. 2021, 170: 108998.

Jokubaitis, S., Celov, D., Leipus, R. Sparse structures with LASSO through Principal Components: forecasting GDP components in the short-run. International Journal of Forecasting. 2021, 37: 759–756.

Research Council of Lithuania. The Development of Mathematical Reasoning in School (No S-DNR-20-7). Prof. R. Norvaiša. 20 April 2021–31 December 2021.

The project is aimed at justifying the necessity to develop the mathematical reasoning in school, to identify necessary conditions for its implementation and to prepare the corresponding means to an end. Specifically the inventory of principal concepts of school mathematics is revised, specified and supplemented; the content of school mathematics is deepened in the areas of creation of word problems as well as promotion of intellectual motivation, and the corresponding teaching materials for teachers in-service as well as for future teachers is prepared. For this aim the latest school mathematics research results are used and further research is evolved.

Main publication:

Norvaiša, R. Magnitude, number and school mathematics. Lietuvos Matematikos Rinkinys. 2021, 62: 1–7.

MAIN R&D&I (RESEARCH, DEVELOPMENT AND INNOVATION) PARTNERS

University of Lille (France)
University of Nantes (France)
Hannover University (Germany)
Queen Mary University of London (U.K.)
Tilburg University (The Netherlands)
Karol Adamiecki University of Economics in Katowice (Poland)
Padova University (Italy)

OTHER RESEARCH ACTIVITIES

Prof. A. Račkauskas –

Prof. M. Radavičius –

Prof. V. Čekanavičius –

Prof. R. Leipus –

Prof. R. Norvaiša –

Prof. V. Bagdonavičius –

Prof. V. Kazakevičius –

  • member of the Lithuanian Mathematical Society.

Assoc. Prof. R. Eidukevičius –

Assoc. Prof. R. Levulienė –

Assoc. Prof. V. Skorniakov–

  • member of the Lithuanian Mathematical Society.

MOST IMPORTANT PARTICIPATION CASES OF RESEARCHERS IN WORKING GROUPS OR COMMISSIONS SET UP BY STATE AUTHORITIES, STATE AND MUNICIPAL INSTITUTIONS AND ORGANISATIONS, AND BUSINESS ENTITIES

  • Prof. R. Leipus: member of the European Mathematical Society European Solidarity Committee; member of the Ethics Committee at the Research Council of Lithuania; member of the Committee of conferment of foreign scientific degree at the Research Council of Lithuania; member of the Institute of Mathematical Statistics (IMS).

CONSULTATIONS PROVIDED BY THE UNIT TO THE PUBLIC OR ECONOMIC ENTITIES

  • Prof. R. Leipus, Prof. R. Račkauskas, Assoc. Prof. J. Markevičiūtė, Assoc. Prof. R. Levulienė, Prof. O. Štikonienė: consultations to the Lithuanian Government on the modelling and short/long-term forecasting of COVID-19 in Lithuania (2020–2021).

MOST IMPORTANT RESEARCH DISSEMINATION ACTIVITIES