The research group is involved in the design, development, implementation and monetisation of solutions that include data science, the Internet of Things (IoT), and artificial intelligence (AI).

The group’s research expertise is rooted in its long-standing work in data-efficient machine learning, modelling of structured and unstructured data, planning of the infrastructure for working with large datasets, high-performance computing systems under conditions and autonomous decision-making systems.

The group’s research topics are focused on understanding and formalising aspects of data-driven intelligent behaviour for use in complex systems. Techniques, along with algorithms and software prototypes, are developed for various applications and represent an increasingly important element in building more robust and intelligent data-based technologies.

The group’s research topics include data management, statistics, machine learning, applying machine learning to natural language processing, applying machine learning to unstructured data processing, probability-based reasoning and the decomposition and application of AI systems. We are a comprehensive research group that combines technical and social sciences with prototype creation, advanced data usage, data modelling, perceptual research of data products, and the design of user experiences for these products.

Academic advisors

  • Prof. Biljana Mileva Boshkoska, PhD
  • Assoc. Prof. Pavle Boškoski, PhD
  • Assoc. Prof. Zoran Levnajić, PhD
  • Assoc. Prof. Goran Klepac, PhD

Papers

  • Dutta, Tulika; Bhattacharyya, Siddhartha; Ketan Panigrahi, Bijaya; Zelinka, Ivan; Mršić, Leo (2023). Multi-level quantum inspired metaheuristics for automatic clustering of hyperspectral images. Q2
  • Koyel Chakraborty, Siddhartha Bhattacharyya, Rajib Bag, Leo Mrsic (2023). Sentiment analysis on labeled and unlabeled datasets using BERT architecture. Q2
  • Dey, A.; Bhattacharyya, S.; Dey, S.; Konar, D.; Platos, J.; Snasel, V.; Mrsic, L.; Pal, P.            A (2023). Review of Quantum-Inspired Metaheuristic Algorithms for Automatic Clustering, Q2
  • Nag, Apala; Pal, Pamnkaj; Bhattacharyya, Siddhartha; Mrsic, Leo; Platos, Jan (2023). A Brief Review on Quantum Blockchain // Human-Centric Smart Computing. Singapore: Springer Singapore
  • Rabuzin, K.; Gulija, D.; Mršić, L. and Modrušan, N. (2023). Towards Semantic Interoperability of Core Registers in Croatia
  • Modrušan, N.; Rabuzin, K.; Mršić, L. (2021). Review of public procurement fraud detection techniques powered by emerging technologies
  • Del Mar-Raave, Joanna Rose; Bahsi, Hayretdin; Mršić, Leo; Hausknec, Krešimir (2021). A machine learning-based forensic tool for image classification – A design science approach Q1
  • Mršić, Leo; Mesić, Tomislav; Balković, Mislav (2020). Cognitive Services Applied as Student Support Service Chatbot for Educational Institution
  • Mršić, Leo; Jerković, Hrvoje; Balković, Mislav (2020). Interactive Skill Based Labor Market Mechanics and Dynamics Analysis System Using Machine Learning and Big Data. Springer

Projects

  • Project title: AI-powered Next Generation of VET (AI4VET4AI)
  • Project title: Artificial Intelligence for PeoplePlanetProfit (AI4PPP)
  • Project title: Unlocking Power of High-Performance Computing through Education (HiPowerEd)
  • Project title: Artificial Intelligence in Medical Care: Reducing Errors and Saving Lives (AI2MED)
  • Project title: Gene pattern analysis and digital support for nutrition planning (NUTRIGENOMIKA365)
  • Project title: Automatic synchronized system for advanced distribution management – a network aimed at preserving reliability and robustness in real time (IRI Research PowerGrid)
  • Project title: Smart Routing and Air Quality Analysis (SMARTenROUTE)
  • Project title: Media Literacy Observatory for Active Citizenship and Sustainable Democracy (MELIA Observatory)
  • Project title: Applied Data Science Educational Ecosystem (ADSEE)

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