Scientific Publications

Publications from MERIT members in the target domains

1st Year

Cybersecurity:

Sharif, Amir; Marino, Francesco Antonio; Sciarretta, Giada; De Marco, Giuseppe; Carbone, Roberto; Ranise, Silvio. Cross-Domain Sharing of User Claims: A Design Proposal for OpenID Connect Attribute Authorities. ARES 2023. https://dl.acm.org/doi/10.1145/3600160.3600183 (ACM Digital Library)
Sharif, Amir; Ranzi, Matteo; Carbone, Roberto; Sciarretta, Giada; Marino, Francesco Antonio; Ranise, Silvio. The eIDAS Regulation: A Survey of Technological Trends for European Electronic Identity Schemes. MDPI Applied Sciences. https://doi.org/10.3390/app122412679 (MDPI)
Stefanovič, Pavel; Ramanauskaitė, Simona. Travel Direction Recommendation Model Based on Photos of User Social Network Profile. IEEE Access, vol. 11, 2023, pp. 28252–28262. https://ieeexplore.ieee.org/document/10077592 (ieeexplore.ieee.org)
Darbutaitė, Ema; Stefanovič, Pavel; Ramanauskaitė, Simona. Machine-Learning-Based Password-Strength-Estimation Approach for Passwords of Lithuanian Context. MDPI Applied Sciences, vol. 13, issue 13 (2023), Article 7811. https://doi.org/10.3390/app13137811 (MDPI)
Kurylets, Anastasiya; Goranin, Nikolaj. Security Ontology OntoSecRPA for Robotic Process Automation Domain. MDPI Applied Sciences, vol. 13, issue 9 (2023), Article 5568. https://doi.org/10.3390/app13095568 (MDPI)
Aliya, Abdiraman; Goranin, Nikolaj; Balevičius, Simas; Nurusheva, Assel; Tumasonienė, Inga. Application of Multicriteria Methods for Improvement of Information Security Metrics. MDPI Sustainability, vol. 15, issue 10 (2023), Article 8114. https://doi.org/10.3390/su15108114 (MDPI)
Kundrotas, Mantas; Janutėnaitė-Bogdanienė, Jūratė; Šešok, Dmitrij. Two-Step Algorithm for License Plate Identification Using Deep Neural Networks. MDPI Applied Sciences, vol. 13, issue 8 (2023), Article 4902. https://doi.org/10.3390/app13084902 (MDPI)
Janutėnas, Laimonas; Janutėnaitė-Bogdanienė, Jūratė; Šešok, Dmitrij. Deep Learning Methods to Detect Image Falsification. MDPI Applied Sciences, vol. 13, issue 13 (2023), Article 7694. https://doi.org/10.3390/app13137694 (MDPI)
Tamulionis, Mantas; Sledevič, Tomyslav; Abromavičius, Vytautas; Kurpytė-Lipnickė, Dovilė; Navakauskas, Dalius; Serackis, Artūras; Matuzevičius, Dalius. Finding the Least Motion-Blurred Image by Reusing Early Features of Object Detection Network. MDPI Applied Sciences, vol. 13, issue 3 (2023), Article 1264. https://doi.org/10.3390/app13031264 (MDPI)
Raju, Dhananjay; Bakirtzis, Georgios; Topcu, Ufuk. Memoryless Adversaries in Imperfect Information Games. In: Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems (AAMAS ’23), pp. 2379–2381. https://dl.acm.org/doi/10.5555/3545946.3598940 (ACM Digital Library)

AI:

Martorell-Marugán, Jordi; Chierici, Marco; Jurman, Giuseppe; Alarcón-Riquelme, Marta E.; Carmona-Sáez, Pedro. Differential diagnosis of systemic lupus erythematosus and Sjögren’s syndrome using machine learning and multi-omics data. Computers in Biology and Medicine. https://doi.org/10.1016/j.compbiomed.2022.106373
Minnai, Francesca; Noci, Sara; Chierici, Marco; Cotroneo, Chiara Elisabetta; Bartolini, Barbara; Incarbone, Matteo; Tosi, Davide; Mattioni, Giovanni; Jurman, Giuseppe; Dragani, Tommaso A.; Colombo, Francesca. Genetic predisposition to lung adenocarcinoma outcome is a feature already present in patients’ non-involved lung tissue. Cancer Science. https://doi.org/10.1111/cas.15591
Chicco, Davide; Jurman, Giuseppe. Ten simple rules for providing bioinformatics support within a hospital. BioData Mining. https://doi.org/10.1186/s13040-023-00326-0
Chicco, Davide; Jurman, Giuseppe. The Matthews correlation coefficient (MCC) should replace the ROC AUC as the standard metric for assessing binary classification. BioData Mining. https://doi.org/10.1186/s13040-023-00322-4
Chicco, Davide; Sanavia, Tiziana; Jurman, Giuseppe. Signature literature review reveals AHCY, DPYSL3, and NME1 as the most recurrent prognostic genes for neuroblastoma. BioData Mining. https://doi.org/10.1186/s13040-023-00325-1
Yamin, Muhammad Abubakar; Valsasina, Paola; Tessadori, Jacopo; Filippi, Massimo; Murino, Vittorio; Rocca, Maria A.; Sona, Diego. Discovering functional connectivity features characterizing multiple sclerosis phenotypes using explainable artificial intelligence. Human Brain Mapping. https://doi.org/10.1002/hbm.26210
Valeri, Federico; Chierici, Marco; Jurman, Giuseppe; et al. UNet and MobileNet CNN-based model observers for CT protocol optimization: comparative performance evaluation by means of phantom CT images. Journal of Medical Imaging. https://doi.org/10.1117/1.JMI.10.S1.S11904
Chierici, Marco; [co-authors]. Automatically detecting Crohn’s disease and Ulcerative Colitis from endoscopic imaging. BMC Medical Informatics and Decision Making. https://doi.org/10.1186/s12911-022-02043-w
Marcolini, Alessia; Bussola, Nicole; Arbitrio, Ernesto; Amgad, Mohamed; Jurman, Giuseppe; Furlanello, Cesare. histolab: A Python library for reproducible Digital Pathology preprocessing with automated testing. SoftwareX. https://www.sciencedirect.com/science/article/pii/S2352711022001558
Chicco, Davide; Alameer, Ali; Rahmati, Sahar; Jurman, Giuseppe. Towards a potential pan-cancer prognostic signature for gene expression based on probesets and ensemble machine learning. BioData Mining. https://doi.org/10.1186/s13040-022-00312-y
Muhammad Abubakar Yamin, Paola Valsasina, Jacopo Tessadori, Massimo Filippi, Vittorio Murino, Maria A Rocca, Diego Sona. Discovering functional connectivity features characterizing multiple sclerosis phenotypes using explainable artificial intelligence. NeuroImage. https://doi.org/10.1016/j.neuroimage.2023.120017
Francesca Minnai, Sara Noci, Marco Chierici, Chiara Elisabetta Cotroneo, Barbara Bartolini, Matteo Incarbone, Davide Tosi, Giovanni Mattioni, Giuseppe Jurman, Tommaso A Dragani, Francesca Colombo. Genetic predisposition to lung adenocarcinoma outcome is a feature already present in patients’ noninvolved lung tissue. Molecular Oncology. https://doi.org/10.1002/1878-0261.13374
Jordi Martorell-Marugán, Marco Chierici, Giuseppe Jurman, Marta E Alarcón-Riquelme, Pedro Carmona-Sáez. Differential diagnosis of systemic lupus erythematosus and Sjögren’s syndrome using machine learning and multi-omics data. Bioinformatics. https://doi.org/10.1093/bioinformatics/btac785
Davide Chicco, Giuseppe Jurman. The Matthews correlation coefficient (MCC) should replace the ROC AUC as the standard metric for assessing binary classification. Bioinformatics. https://doi.org/10.1093/bioinformatics/btad035
A Baragetti, L Grigore, F Pellegatta, E Mattavelli, M Chierici, G Jurman, A Catapano. Targeted proteomics and the presence of carotid plaques in subjects at low cardiovascular disease risk. European Journal of Preventive Cardiology. https://doi.org/10.1093/eurjpc/zwad198
Davide Chicco, Giuseppe Jurman. Ten simple rules for providing bioinformatics support within a hospital. PLOS Computational Biology. https://doi.org/10.1371/journal.pcbi.1010834
Davide Chicco, Giuseppe Jurman. Signature literature review reveals AHCY, DPYSL3, and NME1 as the most recurrent prognostic genes for neuroblastoma. Briefings in Bioinformatics. https://doi.org/10.1093/bib/bbad050
Davide Chicco, Giuseppe Jurman. A statistical comparison between Matthews correlation coefficient (MCC), prevalence threshold, and Fowlkes–Mallows index. Scientific Reports. https://doi.org/10.1038/s41598-023-38290-7
Jankauskas Mindaugas; Serackis Artūras; Šapurov Martynas; Pomarnacki Raimondas; Baškys Algirdas; Hyunh Van Khang; Vaimann Toomas; Zakis Janis. Exploring the limits of early predictive maintenance in wind turbines applying an anomaly detection technique. Sensors. https://doi.org/10.3390/s23125732
Kundrotas Mantas; Mažonienė Edita; Šešok Dmitrij. Automatic tumor identification from scans of histopathological tissues. Applied sciences. https://doi.org/10.3390/app13074127
Gurčinas, Vitalijus; Dautartas, Juozas; Janulevičius, Justinas; Goranin, Nikolaj; Čenys, Antanas. A deep-learning-based approach to keystroke-injection payload generation. Electronics. https://doi.org/10.3390/electronics12132894
Darbutaitė Ema; Stefanovič Pavel; Ramanauskaitė Simona. Machine-learning-based password-strength-estimation approach for passwords of Lithuanian context. Applied sciences. https://doi.org/10.3390/app13137583
Griazev Kiril; Ramanauskaitė Simona. Web page content block identification with extended block properties. Applied sciences. https://doi.org/10.3390/app13095345
Jačionis Tomas; Urbanavičius Vytautas; Katkevičius Andrius; Abromavičius Vytautas; Serackis Artūras; Sledevič Tomyslav; Plonis Darius. UAV detection using thrust engine electromagnetic spectra. Drones. https://doi.org/10.3390/drones6100295
Janutėnas Laimonas; Janutėnaitė-Bogdanienė Jūratė; Šešok Dmitrij. Deep learning methods to detect image falsification. Applied sciences. https://doi.org/10.3390/app13137512
Kalibatienė Diana; Miliauskaitė Jolanta. An effect of user experience on a data-driven fuzzy inference of web service quality. International journal of computers communications & control. https://doi.org/10.15837/ijccc.2023.4.4984
Kalibatienė, Diana; Miliauskaitė, Jolanta; Slotkienė, Asta; Gudas, Saulius. On the development of the web service quality modelling space. Expert systems with applications. https://doi.org/10.1016/j.eswa.2022.118584
Kundrotas Mantas; Janutėnaitė-Bogdanienė Jūratė; Šešok Dmitrij. Two-step algorithm for license plate identification using deep neural networks. Applied sciences. https://doi.org/10.3390/app13084964
Kvietkauskas Tautvydas; Stefanovič Pavel. Influence of training parameters on real-time similar object detection using YOLOv5s. Applied sciences. https://doi.org/10.3390/app13063518
Margienė Asta; Ramanauskaitė Simona; Nugaras Justas; Stefanovič Pavel; Čenys Antanas. Competency-based e-learning systems: Automated integration of user competency portfolio. Sustainability. https://doi.org/10.3390/su142416489
Pozdniakova Olesia; Cholomskis Aurimas; Mažeika Dalius. Self-adaptive autoscaling algorithm for SLA-sensitive applications running on the Kubernetes clusters. Cluster computing. https://doi.org/10.1007/s10586-023-04082-y
Robal, Tarmo; Liiv, Innar; Kalibatienė, Diana; Matulevičius, Raimundas. Special track on Intelligent Systems for Digital Era (ISDE). SAC 2024: Proceedings of the 39th Annual ACM Symposium on Applied Computing. https://doi.org/10.1145/3605098.3647318
Sakavičius Saulius; Serackis Artūras; Abromavičius Vytautas. Multiple sound source localization in three dimensions using convolutional neural networks and clustering based post-processing. IEEE access. https://doi.org/10.1109/ACCESS.2022.3225501
Sielskaitė Šarūnė; Kalibatienė Diana. On fuzzy and case-based dynamic software development process modeling and simulation approach. Applied sciences. https://doi.org/10.3390/app13116543
Sledevič Tomyslav; Serackis Artūras; Plonis Darius. FPGA implementation of a convolutional neural network and its application for pollen detection upon entrance to the beehive. Agriculture. https://doi.org/10.3390/agriculture12111867
Stefanovič Pavel; Ramanauskaitė Simona. Travel direction recommendation model based on photos of user social network profile. IEEE Access. https://doi.org/10.1109/ACCESS.2023.3255955
Tamulionis Mantas; Serackis Artūras; Bartnykas Kęstutis; Miniotas Darius; Mikučionis Šarūnas; Laptik Raimond; Ušinskas Andrius; Matuzevičius Dalius. Improving monocular camera localization for video-based three-dimensional outer ear reconstruction tasks. Applied sciences. https://doi.org/10.3390/app13158712
Tamulionis Mantas; Sledevič Tomyslav; Abromavičius Vytautas; Kurpytė-Lipnickė Dovilė; Navakauskas Dalius; Serackis Artūras; Matuzevičius Dalius. Finding the least motion-blurred image by reusing early features of object detection network. Applied sciences. https://doi.org/10.3390/app13031448
Tamulionis Mantas; Sledevič Tomyslav; Serackis Artūras. Investigation of machine learning model flexibility for automatic application of reverberation effect on audio signal. Applied sciences. https://doi.org/10.3390/app13095318
Vaišis, Vaidotas; Chlebnikovas, Aleksandras; Jasevičius, Raimondas. Numerical study of the flow of pollutants during air purification, taking into account the use of eco-friendly material for the filter—mycelium. Applied sciences. https://doi.org/10.3390/app13031703
Will Chien, Cristian Rodriguez Rivero, Stijn Daniël Haas, Mitchel Molenaar. Echocardiographic Clustering by Machine Learning in Children with Early Surgically Corrected Congenital Heart Disease. ICML 3rd Workshop on Interpretable Machine Learning in Healthcare (IMLH). https://openreview.net/forum?id=LD8wlikwgk
Garstman AG, Rodriguez Rivero C, Onland W. Early Detection of Late Onset Sepsis in Extremely Preterm Infants Using Machine Learning: Towards an Early Warning System. Applied Sciences. https://doi.org/10.3390/app13169049
Kellerhals SA, De Leeuw F, Rodriguez Rivero C. Cloud Nowcasting with Structure-Preserving Convolutional Gated Recurrent Units. Atmosphere. https://doi.org/10.3390/atmos13101632
Baum, Kevin, Joanna Bryson, Frank Dignum, Virginia Dignum, Marko Grobelnik, Holger Hoos, Morten Irgens et al. From fear to action: AI governance and opportunities for all. Frontiers in Computer Science. https://doi.org/10.3389/fcomp.2023.1210421
Raj, R. and Kos, A. An improved human activity recognition technique based on convolutional neural network. Scientific Reports. https://doi.org/10.1038/s41598-023-49779-1
Raj, R. and Kos, A. An optimized energy and time constraints-based path planning for the navigation of mobile robots using an intelligent particle swarm optimization technique. Applied Sciences. https://doi.org/10.3390/app13179667
Raj, R. and Kos, A. A comprehensive study of mobile robot: History, developments, applications, and future research perspectives. Applied Sciences. https://doi.org/10.3390/app12146951
Chiou, Manolis, Serena Booth, Bruno Lacerda, Andreas Theodorou, and Simon Rothfuß. Variable autonomy for human-robot teaming (vat). Companion of the 2023 ACM/IEEE International Conference on Human-Robot Interaction. https://doi.org/10.3390/app13179667

IoT:

Pikner, Heiko; Sell, Raivo; Majak, Jüri; Karjust, Kristo. Safety System Assessment Case Study of Automated Vehicle Shuttle. Electronics. https://doi.org/10.3390/electronics11071162 (MDPI)
Gu, Junyi; Lind, Artjom; Chhetri, Tek Raj; Bellone, Mauro; Sell, Raivo. End-to-End Multimodal Sensor Dataset Collection Framework for Autonomous Vehicles. Sensors. https://doi.org/10.3390/s23156783 (PMC)
Wongpiromsarn, Tichakorn; Ghasemi, Mahsa; Cubuktepe, Murat; Bakirtzis, Georgios; Carr, Steven; Karabag, Mustafa O.; Neary, Cyrus; Gohari, Parham; Topcu, Ufuk. Formal Methods for Autonomous Systems. Foundations and Trends® in Systems and Control. https://doi.org/10.1561/2600000029 (nowpublishers.com)
Bakirtzis, Georgios; Carr, Steven; Danks, David; Topcu, Ufuk. Dynamic certification for autonomous systems. Communications of the ACM. https://doi.org/10.1145/3574133 (OuCi)
Čeponis, Andrius; Mažeika, Dalius; Vasiljev, Piotr; Bareikis, Regimantas. 5-DOF cone-shaped piezoelectric positioning robot for optical systems. Sensors and Actuators A: Physical. https://doi.org/10.1016/j.sna.2023.114280 (gs.elaba.lt)
Čeponis, Andrius; Mažeika, Dalius; Jūrėnas, Vytautas; Deltuvienė, Dovilė; Bareikis, Regimantas. Ring-shaped piezoelectric 5-DOF robot for angular-planar motion. Micromachines. https://doi.org/10.3390/mi13101763 (MDPI)
Navakauskas, Dalius; Kazlauskas, Mantas. Fog computing in healthcare: Systematic review. Informatica. https://doi.org/10.15388/23-INFOR525 (informatica.vu.lt)
Jačionis, Tomas; Urbanavičius, Vytautas; Katkevičius, Andrius; Abromavičius, Vytautas; Serackis, Artūras; Sledevič, Tomyslav; Plonis, Darius. UAV Detection Using Thrust Engine Electromagnetic Spectra. Drones. 2022, 6(10), 1–18. https://doi.org/10.3390/drones6100144 (mdpi.com)
Jačionis, Tomas; Urbanavičius, Vytautas; Katkevičius, Andrius; Abromavičius, Vytautas; Serackis, Artūras; Sledevič, Tomyslav; Plonis, Darius. UAV Detection Using Thrust Engine Electromagnetic Spectra. Drones. 2022, 6(10), 1–18. https://doi.org/10.3390/drones6100144 (mdpi.com)
Antonini, Mattia; Pincheira, Miguel; Vecchio, Massimo; Antonelli, Fabio. An Adaptable and Unsupervised TinyML Anomaly Detection System for Extreme Industrial Environments. Sensors. https://doi.org/10.3390/s23042344 (MDPI)
Pincheira, Miguel; Donini, Elena; Vecchio, Massimo; Kanhere, Salil. A Decentralized Architecture for Trusted Dataset Sharing Using Smart Contracts and Distributed Storage. Sensors. https://doi.org/10.3390/s22239118

2nd Year

AI:

László Makra, István Matyasovszky, Gábor Tusnády, Lewis H Ziska, Jeremy J Hess, László G Nyúl, Daniel S Chapman, Luca Coviello, Andrea Gobbi, Giuseppe Jurman, Cesare Furlanello, Mauro Brunato, Athanasios Damialis, Athanasios Charalampopoulos, Heinz Müller-Schärer, Norbert Schneider, Bence Szabó, Zoltán Sümeghy, Anna Páldy, Donát Magyar, Karl-Christian Bergmann, Áron József Deák, Edit Mikó, Michel Thibaudon, Gilles Oliver, Roberto Albertini, Maira Bonini, Branko Šikoparija, Predrag Radišić, Mirjana Mitrović Josipović, Regula Gehrig, Elena Severova, Valentina Shalaboda, Barbara Stjepanović, Nicoleta Ianovici, Uwe Berger, Andreja Kofol Seliger, Ondřej Rybníček, Dorota Myszkowska, Katarzyna Dąbrowska-Zapart, Barbara Majkowska-Wojciechowska, Elzbieta Weryszko-Chmielewska, Łukasz Grewling, Piotr Rapiejko, Malgorzata Malkiewicz, Ingrida Šaulienė, Olexander Prykhodo, Anna Maleeva, Victoria Rodinkova, Olena Palamarchuk, Jana Ščevková, James M Bullock. A temporally and spatially explicit, data-driven estimation of airborne ragweed pollen concentrations across Europe. Science of The Total Environment. https://doi.org/10.1016/j.scitotenv.2023.166708
Gyamfi Nana Kwame; Goranin Nikolaj; Čeponis Dainius; Čenys Antanas. Automated system-level malware detection using machine learning: A comprehensive review. Applied sciences. https://doi.org/10.3390/app132111908
Skačkauskas Paulius; Karpenko Mykola; Prentkovskis Olegas. Design and implementation of a hybrid path planning approach for autonomous lane change manoeuvre. International journal of automotive technology. https://doi.org/10.1007/s12239-024-00014-w
Stefanovič Pavel; Pliuskuvienė Birutė; Radvilaitė Urtė; Ramanauskaitė Simona. Machine learning model for chatGPT usage detection in students’ answers to open-ended questions: Case of Lithuanian language. Education and information technologies. https://doi.org/10.1007/s10639-024-12589-z
Kapustynska, Viroslava; Abromavičius, Vytautas; Serackis, Artūras; Paulikas, Šarūnas; Ryliškienė, Kristina; Andruškevičius, Saulius. Machine learning and wearable technology: monitoring changes in biomedical signal patterns during pre-migraine nights. Healthcare. https://doi.org/10.3390/healthcare12171701
Abisheva, Gulsipat; Goranin, Nikolaj; Razakhova, Bibigul; Aidynov, Tolegen; Satybaldina, Dina. Specifics of data collection and data processing during formation of RailVista dataset for machine learning- and deep learning-based applications. Sensors. https://doi.org/10.3390/s24165239
Belova-Plonienė, Diana; Krukonis, Audrius; Abromavičius, Vytautas; Serackis, Artūras; Urbanavičius, Vytautas; Katkevičius, Andrius. Meander structure analysis techniques using artificial neural networks. Applied sciences. https://doi.org/10.3390/app14135766
Gyamfi, Nana Kwame; Goranin, Nikolaj; Čeponis, Dainius. An empirical determination of optimum artificial intelligence algorithm: Detection using signal-to-noise ratio approach. IEEE access. https://doi.org/10.1109/ACCESS.2024.3425585
Jankauskas, Mindaugas; Serackis, Artūras; Paulauskas, Nerijus; Pomarnacki, Raimondas; Hyunh, Van Khang. The impact of the weather forecast model on improving AI-Based power generation predictions through BiLSTM networks. Electronics. https://doi.org/10.3390/electronics13173472
Kalibatienė, Diana; Miliauskaitė, Jolanta; Slotkienė, Asta. Ontology and fuzzy theory application in information systems: A bibliometric analysis. Informatica. https://doi.org/10.15388/24-INFOR557
Kvietkauskas, Tautvydas; Pavlov, Ernest; Stefanovič, Pavel; Pliuskuvienė, Birutė. The efficiency of YOLOv5 models in the detection of similar construction details. Applied sciences. https://doi.org/10.3390/app14093946
Pocevičė, Gabija; Stefanovič, Pavel; Ramanauskaitė, Simona; Pavlov, Ernest. Approach for tattoo detection and identification based on YOLOv5 and similarity distance. Applied sciences. https://doi.org/10.3390/app14135576
Pozdniakova, Olesia; Mažeika, Dalius; Cholomskis, Aurimas. SLA-adaptive threshold adjustment for a Kubernetes horizontal pod autoscaler. Electronics. https://doi.org/10.3390/electronics13071242
Robal, Tarmo; Liiv, Innar; Kalibatienė, Diana. EDITORIAL MESSAGE: Special Track on Intelligent Systems for Digital Era (ISDE). Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing, SAC 2023. https://doi.org/10.1145/3555776.3588661
Narigina, M., Romānovs, A., Merkurjevs, J. Convolutional Neural Network-Based Digital Diagnostic Tool for the Identification of Psychosomatic Illnesses. Algorithms. https://doi.org/10.3390/a17080329
Ķempelis, A., Poļaka, I., Romānovs, A., Patļins, A. Computer Vision and Machine Learning-Based Predictive Analysis for Urban Agricultural Systems. Future Internet. https://doi.org/10.3390/fi16020044
Balogh, D., Hudelist, G., Bļizņuks, D., Raghothama, J., Becker, C., Horace, R., Krentel, H., Horne, A., Bourdel, N., Marki, G., Tomassetti, C., Kirk, U., Acs, N., Bokor, A. FEMaLe: The Use of Machine Learning for Early Diagnosis of Endometriosis based on Patient Self-Reported Data—Study Protocol of a Multicenter Trial. PLoS ONE. https://doi.org/10.1371/journal.pone.0300186
Edelmers, E., Kažoka, D., Boločko, K., Sudars, K., Pilmane, M. Automatization of CT Annotation: Combining AI Efficiency with Expert Precision. Diagnostics. https://doi.org/10.3390/diagnostics14020185
Paat, A.; Majak, J.; Karu, V.; Hitch, M. Fuzzy analytical hierarchy process based environmental, social and governance risks assessment for the future phosphorite mining in Estonia. The Extractive Industries and Society. https://doi.org/10.1016/j.exis.2024.101438
Aler Tubella, Andrea, Marçal Mora-Cantallops, and Juan Carlos Nieves. How to teach responsible AI in Higher Education: challenges and opportunities. Ethics and Information Technology. https://doi.org/10.1007/s10676-024-09756-3
Methnani, Leila, Virginia Dignum, and Andreas Theodorou. Clash of the Explainers: Argumentation for Context-Appropriate Explanations. European Conference on Artificial Intelligence (ECAI 2023). https://doi.org/10.3233/FAIA230551
Methnani, Leila, Manolis Chiou, Virginia Dignum, and Andreas Theodorou. Who’s in charge here? A survey on Trustworthy AI in Variable Autonomy Robotic Systems. ACM Computing Surveys. https://doi.org/10.1145/3693444

Cybersecurity:

Benetis, Dovydas; Vitkus, Donatas; Janulevičius, Justinas; Čenys, Antanas; Goranin, Nikolaj. Automated conversion of CVE records into an expert system, dedicated to information security risk analysis, knowledge-base rules. Electronics. https://doi.org/10.3390/electronics13132642
Goranin, Nikolaj; Hora, Simran Kaur; Čenys, Antanas. A bibliometric review of intrusion detection research in IoT: Evolution, collaboration, and emerging trends. Electronics. https://doi.org/10.3390/electronics13163210
Gyamfi Nana Kwame; Goranin Nikolaj; Čeponis Dainius; Čenys Antanas. Automated system-level malware detection using machine learning: A comprehensive review. Applied sciences. https://doi.org/10.3390/app132111624
Kurylets Anastasiya; Goranin Nikolaj. Design and implementation of a UMLRPAsec-Extension for Robotic Process Automation. Electronics. https://doi.org/10.3390/electronics13040776
Olegen Aidynov; Goranin Nikolaj; Satybaldina Dina; Nurusheva Assel. A systematic literature review of current trends in electronic voting system protection using modern cryptography. Applied sciences. https://doi.org/10.3390/app14072844
Vyšniūnas Tolvinas; Čeponis Dainius; Goranin Nikolaj; Čenys Antanas. Risk-based system-call sequence grouping method for malware intrusion detection. Electronics. https://doi.org/10.3390/electronics13010098
Ņikiforova, O., Romānovs, A., Zabiņako, V., Korņijenko, J. Detecting and Identifying Insider Threats Based on Advanced Clustering Methods. IEEE Access. https://doi.org/10.1109/ACCESS.2024.3365424
Pirta-Dreimane, R., Romānovs, A., Bikovska, J., Pekša, J., Vartiainen, T., Valliou, M., Kamsamrong, J., Eltahawy, B. Enhancing Smart Grid Resilience: An Educational Approach to Smart Grid Cybersecurity Skill Gap Mitigation. Energies. https://doi.org/10.3390/en17081876
Pirta, R., Brilingaitė, A., Roponena, E., Parish, K., Grabis, J., Lugo, R., Bonders, M. Try to esCAPE from Cybersecurity Incidents! A Technology-Enhanced Educational Approach. Technology, Knowledge and Learning. https://doi.org/10.1007/s10758-024-09769-8
Brilingaitė, A., Bukauskas, L., Domarkienė, I., Rančelis, T., Ambrozaitytė, L., Pirta, R., Lugo, R., Knox, B. Towards Projection of the Individualised Risk Assessment for the Cybersecurity Workforce. Computer Standards & Interfaces. https://doi.org/10.1016/j.csi.2024.103962
Pirta-Dreimane, R., Brilingaitė, A., Roponena, E., Parish, K., Grabis, J., Lugo, R., Bonders, M. CyberEscape Approach to Advancing Hard and Soft Skills in Cybersecurity Education. Augmented Cognition: 17th International Conference, AC 2023. https://doi.org/10.1007/978-3-031-35017-7_28

IoT:

Čeponis Andrius; Jūrėnas Vytautas; Mažeika Dalius. Low profile triangle-shaped piezoelectric rotary motor. Micromachines. https://doi.org/10.3390/mi15010071
Ma Xinchi; Yang Ying; Qiu Jianmin; Zhang Jiyang; Vasiljev Piotr; Wu Jintao; Mažeika Dalius; Zhao Lei; Borodinas Sergejus; Liu Jikui. A novel rotary ultrasonic motor based on multiple Langevin transducers: design, simulation, and experimental investigation. Smart materials and structures. https://doi.org/10.1088/1361-665X/ad342e
Čeponis Andrius; Jūrėnas Vytautas; Mažeika Dalius; Bakanauskas Vytautas; Deltuvienė Dovilė. Rod-shaped linear inertial type piezoelectric actuator. Actuators. https://doi.org/10.3390/act12100378
Rassolkin, Anton; Maksimkins, Pavels; Stupans, Andrejs; Rjabtsikov, Viktor; Senfelds, Armands; Kuts, Vladimir. Spatial Representation of Self-driving Vehicle for Virtual Entity of Digital Twin. Computer. https://doi.org/10.1109/MC.2023.3319108
Moncunill-Geniz, F.X.; del-Águila-López, F.; Demirkol, I.; Bonet-Dalmau, J.; Palà-Schönwälder, P. Super-Regenerative Receiver Wake-Up Radio Solution for 5G New Radio Communications. Electronics. https://doi.org/10.3390/electronics12245011
Serra, Aleix Llusà, Francisco del Águila López, Jordi Bonet Dalmau, and Xavier Moncunill-Geniz. A new community business model for a free, open, and neutral network: Considering the wireless to fiber transition. Internet of Things. https://doi.org/10.1016/j.iot.2024.101157

3rd Year

Cybersecurity:

Riccardo Germenia, Salvatore Manfredi, Giada Sciarretta, Mario Scuro, Alessandro Tomasi. Comparison of Credential Status Mechanisms for the Digital Wallet Ecosystem. 22nd International Conference on Security and Cryptography (SECRYPT 2025). https://doi.org/10.5220/0013635500003979
Stefano Berlato, Umberto Morelli, Roberto Carbone, Silvio Ranise. A Secure and Quality of Service-Aware Solution for the End to End Protection of IoT Applications. Journal of Network and Computer Applications. https://doi.org/10.1016/j.jnca.2025.104246
Algimantas Venčkauskas; Šarūnas Grigaliūnas; Linas Pocius; Rasa Brūzgienė; Andrejs Romanovs. Machine Learning in Money Laundering Detection Over Blockchain Technology. IEEE Access. https://doi.org/10.1109/ACCESS.2024.3452003
Raamets, Tõnis; Karjust, Kristo; Majak, Jüri; Hermaste, Aigar. Implementing an AI-Based Digital Twin Analysis System for Real-Time Decision Support in a Custom-Made Sportswear SME. Applied Sciences. https://doi.org/10.3390/app15147952

AI:

Riello, Marianna; Moroni, Monica; Bovo, Stefano; Ragni, Flavio; Buganza, Manuela; Di Giacopo, Raffaella; Chierici, Marco; Gios, Lorenzo; Pardini, Matteo; Massa, Federico; Dallabona, Monica; Vanzetta, Elisa; Campi, Cristina; Piana, Michele; Garbarino, Sara; Marenco, Manuela; Osmani, Venet; Jurman, Giuseppe; Uccelli, Antonio; Giometto, Bruno. Neuropsychological and clinical variables associated with cognitive trajectories in patients with Alzheimer’s disease. Frontiers in Aging Neuroscience. https://doi.org/10.3389/fnagi.2025.1565006
Cazzolli, Carlotta; Chierici, Marco; Dallabona, Monica; Guella, Chiara; Jurman, Giuseppe. Neuropsychological tests and machine learning: identifying predictors of MCI and dementia progression. Aging Clinical and Experimental Research. https://doi.org/10.1007/s40520-025-02962-4
Gios, Lorenzo; Chierici, Marco; Moroni, Monica; Jurman, Giuseppe; Osmani, Venet. Artificial intelligence of imaging and clinical neurological data for predictive, preventive and personalized (P3) medicine for Parkinson Disease: The NeuroArtP3 protocol for a multi-center research study. PLOS One. https://doi.org/10.1371/journal.pone.0300127
Jordi Martorell-Marugán, Raúl López-Domínguez, Juan Antonio Villatoro-García, Daniel Toro-Domínguez, Marco Chierici, Giuseppe Jurman, Pedro Carmona-Sáez. Explainable deep neural networks for predicting sample phenotypes from single-cell transcriptomics. Briefings in Bioinformatics. https://doi.org/10.1093/bib/bbae673
Jacopo Tessadori, Ilaria Boscolo Galazzo, Silvia F Storti, Lorenzo Pini, Lorenza Brusini, Federica Cruciani, Diego Sona, Gloria Menegaz, Vittorio Murino. Linking dynamic connectivity states to cognitive decline and anatomical changes in Alzheimer’s disease. Neuroimage. https://doi.org/10.1016/j.neuroimage.2025.121448
Davide Chicco, Alessandro Fabris, Giuseppe Jurman. The Venus score for the assessment of the quality and trustworthiness of biomedical datasets. BioData Mining. https://doi.org/10.1186/s13040-024-00412-x
Maria Chiara Malaguti, Lorenzo Gios, Giuseppe Jurman. The third wheel or the game changer? How AI could team up with neurologists in Parkinson’s care. Parkinsonism & Related Disorders. https://doi.org/10.1016/j.parkreldis.2025.107797
Maria Chiara Malaguti, Chiara Longo, Monica Moroni, Flavio Ragni, Stefano Bovo, Marco Chierici, Lorenzo Gios, Laura Avanzino, Roberta Marchese, Francesca Di Biasio, Matteo Pardini, Denise Cerne, Paola Mandich, Manuela Marenco, Antonio Uccelli, Bruno Giometto, Giuseppe Jurman, Venet Osmani; NeuroArtP3 Network. Machine Learning Predicts Risk of Falls in Parkison’s Disease Patients in a Multicenter Observational Study. European Journal of Neurology. https://doi.org/10.1111/ene.70118
Matteo Pozzi, Shahryar Noei, Erich Robbi, Luca Cima, Monica Moroni, Enrico Munari, Evelin Torresani & Giuseppe Jurman. Generating and evaluating synthetic data in digital pathology through diffusion models. Scientific Reports. https://doi.org/10.1038/s41598-024-79602-w
Flavio Ragni, Stefano Bovo, Andrea Zen, Diego Sona, Katia De Nadai, Ginevra Giovanna Adamo, Marco Pellegrini, Francesco Nasini, Chiara Vivarelli, Marco Tavolato, Marco Mura, Francesco Parmeggiani, Giuseppe Jurman. Session-by-Session Prediction of Anti-Endothelial Growth Factor Injection Needs in Neovascular Age-Related Macular Degeneration Using Optical-Coherence-Tomography-Derived Features and Machine Learning. Diagnostics. https://doi.org/10.3390/diagnostics14232609
Ermanno Cordelli, Paolo Soda, Sara Citter, Elia Schiavon, Christian Salvatore, Deborah Fazzini, Greta Clementi, Michaela Cellina, Andrea Cozzi, Chandra Bortolotto, Lorenzo Preda, Luisa Francini, Matteo Tortora, Isabella Castiglioni, Sergio Papa, Diego Sona & Marco Alì. Machine learning predicts pulmonary Long Covid sequelae using clinical data. BMC Medical Informatics and Decision Making. https://doi.org/10.1186/s12911-024-02745-3
Sledevič, Tomyslav; Serackis, Artūras; Matuzevičius, Dalius; Plonis, Darius; Andriukaitis, Darius. Keypoint-based bee orientation estimation and ramp detection at the hive entrance for bee behavior identification system. Agriculture. https://doi.org/10.3390/agriculture14111890
M. Narigina, A. Romanovs and Y. Merkuryev. A Review of AI-Driven Digital Twin Frameworks for Cardiovascular Disease Diagnosis and Management. 2024 IEEE 65th International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS). https://doi.org/10.1109/ITMS64072.2024.10741948
Edelmers E, Ņikuļins A, Sprūdža KL, Stapulone P, Pūce NS, Skrebele E, Siņicina EE, Cīrule V, Kazuša A, Boločko K. AI-Assisted Detection and Localization of Spinal Metastatic Lesions. Diagnostics (Basel). https://doi.org/10.3390/diagnostics14212458
Nikulins, A.; Edelmers, E.; Sudars, K.; Polaka, I. Adapting Classification Neural Network Architectures for Medical Image Segmentation Using Explainable AI. J. Imaging. https://doi.org/10.3390/jimaging11020055
Narigina, M.; Vindecs, A.; Bošković, D.; Merkuryev, Y.; Romanovs, A. AI-Powered Stroke Diagnosis System: Methodological Framework and Implementation. Future Internet. https://doi.org/10.3390/fi17050204
M. Narigina, A. Vindecs and A. Romanovs. Cycling-Related Diseases and the Role of Automation in Their Diagnosis: A Comprehensive Review. 2025 IEEE 12th Workshop on Advances in Information, Electronic and Electrical Engineering (AIEEE). https://doi.org/10.1109/AIEEE66149.2025.11050760
Raj, R. and Kos, A. Intelligent mobile robot navigation in unknown and complex environment using reinforcement learning technique. Scientific Reports. https://doi.org/10.1038/s41598-024-72857-3
Raj, R. and Kos, A. An Extensive Study of Convolutional Neural Networks: Applications in Computer Vision for Improved Robotics Perceptions. Sensors. https://doi.org/10.3390/s25041033
Chouaten K, Rodriguez Rivero C, Nack F and Reckers M. Unlocking high-value football fans: unsupervised machine learning for customer segmentation and lifetime value. Front. Sports Act. Living. https://doi.org/10.3389/fspor.2024.1362489

IoT:

Paolo Grazieschi, Massimo Vecchio, Miguel Pincheira, Fabio Antonelli. Soilcast: a Multitask Encoder-Decoder AI Model for Precision Agriculture. The 40th ACM/SIGAPP Symposium On Applied Computing (SAC 2025). https://doi.org/10.1145/3673551.3697193
Abderrahim Khiari, Anas Osman, Massimo Vecchio, Mattia Antonini, Miguel Pincheira. Toward Compliance and Transparency in Raw Material Sourcing With Blockchain and Edge AI. IEEE Access. https://doi.org/10.1109/ACCESS.2025.3533860
Sudņiks, R., Ziemelis, A., Ņikitenko, A., Soares, V., Supe, A. Indoor Microclimate Monitoring and Forecasting: Public Sector Building Use Case. Information. https://doi.org/10.3390/info16020121
Telicko, J.; Krumins, A.; Nikitenko, A. Development and Evaluation of Neural Network Architectures for Model Predictive Control of Building Thermal Systems. Buildings. https://doi.org/10.3390/buildings15152702
Karjust, Kristo; Mehrparvar, Marmar; Kaganski, Sergei; Raamets, Tõnis. Development of a Sustainability-Oriented KPI Selection Model for Manufacturing Processes. Sustainability. https://doi.org/10.3390/su17146374
D. Bhandari, A. Agarwal, R. Reena Roy, R. Priyatharshini and R. Rivero Cristian. A Web-Based Interface That Leverages Machine Learning to Assess an Individual’s Vulnerability to Brain Stroke. IEEE Access. https://doi.org/10.1109/ACCESS.2025.3566093
Valentina Navarro-Ovando, Sterre van Schie, Imme Garrelfs, Jop Rijksbaron, Cristian Rodriguez Rivero, Ron Mathôt, Glenn Dumont. Current approaches using remote monitoring technology in alcohol use disorder (AUD): an integrative review. Alcohol and Alcoholism. https://doi.org/10.1093/alcalc/agaf032