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Intelligent Technologies Research Group
Address
Akademijos st. 4, room 619
Vilnius, Lithuania
Head of the Group
dr. Virginijus Marcinkevičius
Research fields
Group research interests:
- Machine learning and its application
- Artificial intelligence and its application
- Natural language processing
- Cyber security
- Mathematical modeling
- Image analysis
- Hyperspectral 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 theme
Research theme "Theoretical and applied aspects of machine learning and mathematical modelling (2019–2023)"
Physical Sciences (Informatics) 41-T-12, Technological Sciences (Informatics Engineering) 42-E-4
Main goal
Develop and explore models based on machine learning and mathematical modelling for cyber security, anomalous data detection, real-time data classification, prediction, and explanation of results.
Tasks in 2023:
- The suitability of deep learning algorithms for hyper-spectral data analysis.
- Image similarity evaluation study using deep Siamese neural networks.
- Development of fraud site detection algorithms.
- A review of gene mutation prediction algorithms.
- Overview of propaganda detection algorithms.
- An application of semantic analysis and machine learning algorithms for password guessing.
- Content recognition in digitally structured documents. Study of inequalities for zeta functions.
- Study of limit theorems for combinatorial numbers.
- Efficient algorithms for visualization of Mandelbrot shells associated with the Ryman zeta function.
- Securities price forecasting and investment portfolio formation using machine learning algorithms.
- Geometric topology, number theory and algorithms.
Tasks in 2022:
- Applicability of machine learning algorithms to hyper-spectral data development for analysis.
- Examination of image similarity using Siamese neural networks.
- Modelling the behaviour of social systems in critical conditions.
- Imitative modelling of social cohesion and radicalization phenomena.
- Application of text semantic analysis and machine learning algorithms for guessing passwords.
- Context recognition in digitally structured documents.
- Prove limit theorems for numbers in the class of triangular arrays.
- Limit theorems for mixed-type open service networks.
- Open service networks operating under low load conditions.
- Modelling and simulation of social behaviour phenomena.
Tasks in 2021:
- Application of machine learning for hyperspectral image analysis.
- GAN networks for phishing URL detection.
- Modeling multi-phase systems.
- Investigation of open computer networks when network load is small.
- Stable modeling in finance engineering.
- Practical aspects of Central limit theorem Borvein algorithm
Tasks in 2019-2020:
- Application of machine learning in anomalous network data detection
- Adapting heavy tail models to identify abnormalities in security tasks of computer networks
- Modification of classification algorithms for CERN data certification
- Critical region inequalities for Riemann zeta function modules
- Create a recursive algorithm for the recognition of the parameters of the Wiener process monitored with noise
- Create a recursive algorithm for multi-dimensional Dirichlet distribution parameter recognition
- Testing and matching metrics and an agent-based model for measuring the impact of cultural processes on social capital to create a functional simulation prototype
- Get the primary results in the theory of networks with different performance nodes
Science and Education
Courses taught
Courses taught to VU doctoral students
| Courses | Co-supervisors | |
| Informatics (N 009) studies program | ||
| Research Methods and Methodology of Informatics and Informatics Engineering | A. Lupeikienė, A. Čaplinskas, S. Gudas, V. Marcinkevičius, I. Belovas | |
| Fundamental methods of informatics and computer engineering | J. Žilinskas, O. Kurasova, P. Treigys, L. Laibinis, A. Jakaitienė, R. Baronas, V. Marcinkevičius | |
| Statistical modeling and stochastic optimization | I. Belovas, S. Minkevičius, J. Vaičiulytė | |
| Informatics engineering (T 007) studies program | ||
| Research Methods and Methodology of Informatics and Informatics Engineering | A. Lupeikienė, A. Čaplinskas, S. Guda, V. Marcinkevičius, I. Belovas | |
| Fundamental methods of informatics and computer engineering | J. Žilinskas, O. Kurasova, P. Treigys, L. Laibinis, A. Jakaitienė, R. Baronas, V. Marcinkevičius | |
| Natrual language processing | V. Marcinkevičius, G. Korvel, G. Tamulevičius | |
| Machine learning | V. Marcinkevičius, J. Bernatavičienė, V. Valaitis | |
| Module projects | ||
| Planning of experimental research and processing of the results | I. Belovas, V. Marcinkevičius, A. Jakaitienė | |
| Efficient Algorithms for Calculation of Special Functions | I. Belovas, V. Marcinkevičius, M. Sabaliauskas | |
| Courses taught to VU bachelor students | ||
| Courses | Co-supervisors | |
| Information systems engineering studies program | ||
| Information Security Fundamentals | I. Belovas | |
| Natural language processing | V. Marcinkevičius | |
| Database management systems | R. Savukynas | |
| Computer networks | R. Savukynas | |
| Information systems and cyber security program (Kaunas faculty) | ||
| Digital Forensics | A. Chaževskas | |
| Topics of VU doctoral studies | ||
| Courses | Co-supervisors | |
| Informatics (N 009) | ||
| Computational modeling of physical, chemical, biological and social systems | D. Plikynas | |
| Big data mining | I. Belovas, V. Marcinkevičius, A. Jakaitienė, V. Medvedev, E. Pranckevičienė, O. Vasilecas, J. Žilinskas | |
| Artificial intelligence and machine learning | I. Belovas, V. Marcinkevičius, D. Plikynas, J. Bernatavičienė, G. Dzemyda, O. Kurasova, V. Medvedev, G. Tamulevičius, P. Treigys | |
| Operations research | I. Belovas, L. Sakalauskas | |
| Artificial neural networks, deep learning | V. Marcinkevičius, J. Bernatavičienė, G. Dzemyda, O. Kurasova, V. Medvedev, G. Tamulevičius, P. Treigys | |
| Informatics engineering (T 007) | ||
| Computer-based systems modelling and optimisation | D. Plikynas, L. Sakalauskas | |
| Computational intelligence in economics, medicine and other domains | I. Belovas, V. Marcinkevičius, J. Bernatavičienė, G. Dzemyda, A. Jakaitienė, O. Kurasova, J. Žilinskas | |
| Block chain technologies and cybersecurity | I. Belovas, V. Marcinkevičius, E. Filatovas, R. Paulavičius, V. Medvedev | |
| Artificial intelligence-based image, audio and streaming data processing technologies | I. Belovas, V. Marcinkevičius, L. Sakalauskas, J. Bernatavičienė, G. Korvel, G. Tamulevičius, P. Treigys | |
| Machine learning and natural language processing | V. Marcinkevičius, G. Korvel, G. Tamulevičius | |
| Mathematics (N001) | ||
| Artificial intelligence and mathematical finance | I. Belovas, V. Marcinkevičius | |
Phd Students
| Name, Surname | Supervisor | Field of study |
Theme | Time of study |
| Aivaras Bielskis | Prof. Dr. Igoris Belovas | N 009 | Stock price forecasting and investment portfolio formation using machine learning algorithms |
2022-2026 |
| Mantas Briliauskas | Prof. Dr. Virginijus Marcinkevičius | T 007 | Autonomous Exploration of Unknown Indoor Environments for Micro Aerial Vehicles |
2022-2026 |
| Andrius Chaževskas | Prof. Dr. Igoris Belovas | N 009 | Application of Text Semantic Analysis and Machine Learning Algorithms for Passwords Guessing |
2020-2026 |
| Vytautas Dulskis | Prof. Habil. Dr. Leonidas Sakalauskas | N 009 | Development and Application of Algorithms for Filtering, Identification and Real-Time Control of Stochastic Dynamical Systems Observed with Noise |
2018-2024 |
| Rolandas Gricius | Prof. Dr. Igoris Belovas | N 009 | Recognising the Contents in Digitised Structured Documents |
2021-2025 |
| Saulius Grigaitis | Prof. Dr. Igoris Belovas | N 009 | Speeding up Blockchains Using Non-Random Transactions |
2018-2025 |
| Shubham Juneja | Prof. Dr. Virginijus Marcinkevičius | N 009 | An Investigation of Deep Imitation Learning for Mobile Robot Navigation |
2020-2024 |
| Vytautas Paura | Prof. Dr. Virginijus Marcinkevičius, Consultant Assoc. Prof. Dr. Valdas Rapševičius |
N 009 | Research of Hyperspectral Unmixing Algorithms for the Chemical Composition of Substances |
2020-2024 |
| Ieva Rizgelienė | prof. dr. Darius Plikynas | N 009 | Propaganda Detection and Classification in Social Media Messages Using Hybrid Deep Learning and Semantic Analysis Methods |
2022-2026 |
| Brendonas Stakauskas | Prof. Dr. Virginijus Marcinkevičius | T 007 | Application of Deep Neural Network-Based Machine Learning Methods to Predict the Trajectory of Viral Mutations |
2022-2026 |
| Neringa Urbonaitė | Prof. Habil. Dr. Leonidas Sakalauskas | N 009 | Fractal Brownian Fields and Their Application to Multidimensional Data Modelling |
2019-2025 |
| Paulius Vaitkevičius | Prof. Dr. Virginijus Marcinkevičius | T 007 | Machine Learning Based Open Source Intelligence Information Extraction and Analysis Methods |
2018-2025 |
History
The group was founded in November 2018 (Head of the Group Dr. Virginijus Marcinkevičius) by reorganizing Operational Research Sector.
At the begining of 2019 ITRG staff was as follows: Head of the Group – Senior Researcher Dr. Virginijus Marcinkevičius, Principal Researcher Prof. Dr. Rimvydas Laužikas, Principal Researcher Prof. Dr. Habil. Leonidas Sakalauskas, Senior Researcher Assoc. Prof. Dr. Saulius Minkevičius, Senior Researcher Prof. Dr. Darius Plikynas, Researcher Assoc. Prof. Dr. Igoris Belovas, Junior Researcher Arūnas Miliauskas, Affiliated Researcher Stasys Steišūnas, Specialist Vytautas Dulskis, Specialist Dr. Gintautas Jakimauskas, Project Senior Specialist Povilas Jurčys, Administrator, Chief Specialist, Project Specialist, Project Administrator Snieguolė Meškauskienė, Senior Specialist, Project Administrator Laimutė Mikalauskienė, Junior Researcher, Specialist, Assistant, Senior Project Specialist Dr. Martynas Sabaliauskas, Project Procurement Expert Karolis Urbanavičius, Project Expert Vilma Zubaitienė.
Dissertations
List of defended dissertations:
- Vytautas Jakštys (2018) Application of Contour Detection Methods to Lateral Chromatic Aberration Reduction in Eye Fundus Images and Road Surface Defect Detection (abstract).
- Tomas Pranckevičius (2017) Investigation Of Multi-Class Classification Methods For Textual Data (abstract).
- Edgaras Artemčiukas (2017) Hybrid Object Tracking Method For Augmented Reality Systems Using The Kalman Filter (abstract).
- Martynas Sabaliauskas (2017) Computerized Modeling Technology Of Unique Footwear Surface Manufacturing Design (abstract).
- Ingrida Vaičiulytė (2014) Study and Application of Markov Chain Monte Carlo Method (abstract).
- Valerijonas Dumskis (2014) Analysis and Application of Methods for Search of Stochastic Equilibrium (abstract).
- Loreta Savulionienė (2014) Association Rules Search in Large Data Bases (abstract).
- Gintautas Jakimauskas (2014) Analysis and Application of Empirical Bayes Methods in Data Mining (abstract).
- Saulius Preidys (2012) The Application of Datamining Methods to Personalised Learning Environments (abstract).
- Liudas Kaklauskas (2012) Study and Application of Methods of Fractal Processes Monitoring in Computer Networks (abstract).
- Audrius Kabašinskas (2008) Statistical Analysis of Financial Markets and Methods of Statistical Modeling (abstract).
- Kęstutis Žilinskas (2007) Investigation of Stochastic Linear Programming by Monte Carlo Method (abstract).
- Vaida Bartkutė (2007) Application of Order Statistics for Testing Optimality in Search Algorithms [in Lithuanian].
- Donatas Bakšys (2007) Analysis of Modelling and Optimization Methods for Electronic Interbank Settlements [in Lithuanian].
- Gražvydas Felinskas (2007) Analysis and Application of Heuristic Metods for Optimization of Resource Constrained Schedules [in Lithuanian].
Projects
ITRG from March 28, 2018 to March 31, 2021, carries out the project “Development of Integrated Lithuanian Language and Writing Resources Information System – Raštija 2“.
Project code: Raštija-2, 02.3.1-CPVA-V-527-01-0005.
Programme: 2014–2020 Operational Programme for the European Union Funds’ Investments Priority 2 “Promoting Information Society” 02.3.1-CPVA-V-527 measure „Lithuanian language in information technologies“.
Chief executive: Virginijus Marcinkevičius (, 8~5 210 3911).
Chief financial officer: Algimantas Paliukėnas.
ITRG from September 1, 2017 to December 30, 2019, carries out the project „Development of social impact metrics, conceptual and simulation model of cultural processes“.
Project code: S-MIP-17-2/LSS-580000-1086.
Programme: Programme for funding research teams by Lithuanian Science Council.
Chief executive: Darius Plikynas (, +370 620 95101).
Chief financial officer: Nijolė Kavarskienė.
Conferences
Under the initiative of ITRG, an International and EURO Mini conference „Modelling and Simulation of Social-Behavioral Phenomena in Creative Societies“) will be held from September 18, 2019 to September 30, 2019, www.msbc2019.mii.vu.lt (responsible person Prof. Dr. Habil. Leonidas Sakalauskas (, 8~5 2109323)).
Services
Scientific and expert services:
- modelling and optimization of interbank transactions; optimization of ATM network;
- application of stochastic and heuristic methods to solution of logistics, supply and transport problems.