
About
Mihai Suciu is an Associate Professor at the Department of Computer Science, within the Faculty of Mathematics and Computer Science at Babeș-Bolyai University in Cluj-Napoca, Romania.
Research Interests: His work focuses on the intersection of evolutionary optimization, machine learning (particularly binary classification), and game theory applied to network analysis. Key areas include:
- Game-theoretic models for classification and feature selection
- Extremal optimization algorithms for network problems
- Shapley value applications in influence maximization
- Critical node detection in weighted/hypergraphs
Article Trends: Recent publications emphasize hybridizing game-theoretic concepts (e.g., Nash equilibrium, Shapley value) with evolutionary algorithms to address classification, feature selection, and network robustness. Techniques like noisy extremal optimization and decision forests are recurrent themes.
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