Department of Applied Mathematics

Department of Applied Mathematics specializes in:

• Mathematical methods in the study of signals complexity.
• Application of matrix time series analysis in investigation of dynamical systems and cardiology.
• Fragmentation and research of numerical sequences.
• Blockchains and cryptography.
• Investigation of symmetric and asymmetric cryptographic systems.
• Development and investigation of the efficient digital image encoding, analysis and synthesis techniques.
• Analytical investigation of delay systems.
• Solution of the eigenvalue problem for some matrices with special structure.
• Multivariate data analysis using projection pursuit.
• Research and applications of artificial intelligence methods.

Research groups operating in the Department of Applied Mathematics:

Artificial intelligence, data analytics and modeling, head prof. Dr. Robert Alzbutas

Development and analysis of identification and cryptography methods, head prof. Dr. Eligius Sakalauskas

The Department of Applied Mathematics conducts research and provides services in the following areas:

• Data analytics.
• Reliability theory application.
• Risk and uncertainty analysis.
• Modelling of extreme phenomena and events.
• Development of smart tools for information integration.
• Applied research of cryptographic systems.
• Development and implementation of cryptographic algorithms.

Application of data mining methods in various areas.

International study and research projects carried out by the researchers from the department of Applied mathematics:

• EU COST TD1405 “European Network for the Joint Evaluation of Connected Health Technologies (ENJECT)”. Member of the management committee dr. R. Alzbutas, deputy dr. L. Bikulčienė. Coordinator – University College Dublin (Ireland), 2014–2018.
• “DILPROT: Diabetic kidney disease prediction technology”. Managers: dr. R. Alzbutas (KTU) and dr. Dž. Veličkienė (LSMU). Other executors from FMNS – dr. Tomas Iešmantas.
• EU COST CA15120, “Open Multiscale Sytems in Medicine (OpenMultiMed)”. Member of the management committee dr. T. Iešmantas, deputy dr. R. Alzbutas. Coordinator – Universiteit Masstricht, Maastricht (Netherlands), 2016–2020.
• EU COST CA18208 „ Novel tools for test evaluation and disease prevalence estimation (HARMONY)“. Member of the management committee dr. T. Iešmantas, 2019–2023.
• ITEA3 project „INNO4HEALTH – Stimulate continuous monitoring in personal and physical health“. Manager dr. Liepa Bikulčienė, 2021–2023.
• EU COST CA20124 “Maximising impact of multidisciplinary research in early diagnosis of neonatal brain injury (AI-4-NICU)”. Member of the management committee dr. R. Alzbutas, 2021–2025.

Participation of students in scientific activities (2020-2023)

EU Structural Funds projects financed by the European Social Fund:

1. S-ST-22-28 Development and application of machine learning methods in assessing the risk of mortality of prostate cancer patients. Doc. dr. Tomas Ruzgas (2022-09-05 – 2023-03-31)
2. P-SV-22-86 Security analysis of block cipher operating in CTR mode. Doc. dr. Aleksejus Michalkovič (2022-07-01 – 2022-08-31)
3. P-SV-22-23 Development and research of statistical hypothesis testing criteria. Doc. dr. Tomas Ruzgas (2022-07-01 – 2022-08-31)
4. 09.3.3-LMT-K-712-22-0133 Development of decision support models and an interactive system for assessing the mortality risk of patients diagnosed with prostate cancer. Doc. dr. Tomas Ruzgas (2020-11-03–2021-04-30)