Advanced Algorithms and Optimization Models Supported by Mathematical Theory (OptimaAI)

Basic Information

The OptimaAI project focuses on the development of innovative artificial intelligence algorithms and optimization models grounded in modern mathematical theories. The aim of the project is to build energy-efficient and scalable solutions for the analysis of complex data in bioinformatics, natural language processing, visual tracking, and industrial optimization. A key component of the project is the strong synergy between applied AI technologies (deep learning, NLP, edge AI) and fundamental mathematical disciplines (combinatorics and discrete mathematics, number theory, and group theory).

The project is structured around four work packages: WP1 – Development of advanced bioinformatics tools for single-cell transcriptome analysis; WP2 – Development of AI models for large-scale datasets and intelligent real-time camera signal processing; WP3 – Deep learning for combinatorial optimization and graph theory; and WP4 – Solving mathematical problems applicable to optimization through heuristics and metaheuristics using theoretical, combinatorial, and discrete approaches.

Expected results include open-source software, high-impact scientific publications, and the transfer of results into applications relevant to healthcare, industry, and the digital transition.

Project duration: 1.10.2025 – 30.9.2029.

Publications

1. D. Krupić, D. Matijević, N. Šuvak, J. Maltar, D. Ševerdija, Evaluating the agreement between human preferences, GPT-4V and Gemini Pro Vision assessments: Can AI recognize what people might like?, Computers in Human Behavior: Artificial Humans 6 (2025)

Conferences

Mobility

• Bartol Borozan, Faculty of Informatics and Data Science, University of Regensburg, Germany, 1.10.2025. – 30.06.2026.

News