The research line in Advanced Machine Learning and Intelligent Optimization for Complex Systems (A³O-Intelligence) focuses on the development, analysis, and application of machine learning techniques and optimization methods based on artificial intelligence to address real-world challenges across multiple domains.
This line integrates both fundamental research —including the proposal of new algorithms and methodological approaches, such as DoME (Development of Mathematical Expressions), evolutionary variants, and hybrid learning methods— as well as applied research aimed at solving complex problems in contexts of high social and technological impact. Among the application areas are:
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Medicine and digital health: analysis of biomedical signals and images using deep learning and hybrid techniques for computer-aided diagnosis and predictive models.
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Civil engineering and smart infrastructure: modeling and optimization of complex systems using ML techniques and evolutionary methods.
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Unmanned aerial vehicle swarms (UAVs/drones): trajectory planning, coordination, and control through reinforcement learning and adaptive algorithms.
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Federated Learning and distributed systems: design of efficient schemes for collaborative learning in heterogeneous environments.
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Prediction and alert systems for environmental phenomena (such as harmful algal blooms —HABs): predictive models based on machine learning for prevention and management.
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Smart logistics and process optimization: application of ML techniques for automated decision-making and resource planning.
The A³O-Intelligence line explores synergies between advanced data processing, evolutionary computation, deep learning, and optimization algorithms, with a comprehensive approach that ranges from theoretical formulation to implementation and evaluation in real-world problems. The variety of application contexts reflects the commitment to transferring scientific knowledge into effective solutions in sectors with high impact potential.
The members would be:
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Daniel Rivero Cebrián (Principal Investigator)
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Enrique Fernández Blanco (Principal Investigator)
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Alejandro Puente Castro (Researcher)
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Andrés Molares Ulloa (Researcher)
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Iván Ramírez Morales (External Researcher)
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Jonathan Aguilar (PhD Candidate)
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Kary García (PhD Candidate)
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Pedro Guijas Bravo (PhD Candidate)
Regarding collaborating entities, we have the following:
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CSIC
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INTECMAR
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Technical University of Machala
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Blekinge Institute of Technology
En cuanto a entidades colaboradoras tenemos las siguientes:
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CSIC
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INTECMAR
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Universidad Técnica de Matchala
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Blekinge Institute of Technology