The Metaheuristics for Complex Systems (MECO) research group is a multidisciplinary group that brings together expertise in metaheuristic-based computation, computational intelligence, machine learning and complex systems. The group's research interests focus on modeling, analyzing and developing metaheuristic-based computational techniques from theoretical studies and empirical investigations to real-world applications. MECO group members have extensive experience in the development of various computational intelligence models, hybrid algorithms and machine learning techniques and their application in the context of complex systems and problems.

Research interests

breast cancer (13) complex networks (19) computer-assisted diagnosis (12) critical node detection (5) data mining (48) education (5) evolutionary computing (48) features (16) game theory (7) gui element detection (5) image segmentation (6) large language models (8) machine learning (123) magnetic resonance imaging (9) malicious urls (5) mammographic image (11) metrics (9) mobile (9) nash equilibrium (9) natural language processing (7) object detection (6) optimization (10) railway (4) reinforcement learning (4) sentiment analysis (6) software architectures (10) software engineering (5) synthetic data generation (6) texture analysis (4) web (5)