Prof. Daniel Gonzalez Cortes
Professor — Institut Supérieur de Gestion, FranceResearchGate · Google Scholar · LinkedIn
Prof. Daniel González Cortés is a researcher affiliated with NEOMA Business School in France, specialising in the application of artificial intelligence, machine learning, and data science to financial systems and business management. His recent peer-reviewed publications include work on autoencoder-enhanced clustering for financial time series (IEEE Access, 2024), explainable reinforcement learning for portfolio construction (Expert Systems, 2024), and AI-driven forecasting of financial time series, reflecting deep expertise at the intersection of AI and quantitative finance.
Prof. González Cortés has co-authored publications with researchers at the University of Deusto, Brunel University London, and NEOMA Business School, and has presented his work at leading IEEE and international venues. His research contributes to the growing field of explainable and responsible AI in finance, addressing how machine learning models can be made interpretable for investment and risk management decision-making.
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