Trustworthy AI, Responsible AI, numerical optimization, Explainable AI

I am a former Marie Skłodowska-Curie Actions IF and currently serve as a Full Professor specializing in Artificial Intelligence. My research focuses on the development of trustworthy, explainable, and optimization-driven Artificial Intelligence methods, with particular expertise in machine learning, mathematical optimization, and responsible Artificial Intelligence.

My work is domain-agnostic, emphasizing the design of novel Artificial Intelligence and machine learning methodologies that can be applied across diverse sectors rather than being limited to a single application area. Over the years, I have developed optimization-based machine learning models and decision-support systems for a wide range of domains, including finance, healthcare, manufacturing, energy, transportation, cybersecurity, and smart systems.

In addition to academic research, I actively contribute to international Artificial Intelligence governance and standardization initiatives. I serve as an expert in European Committee for Standardization/European Committee for Electrotechnical Standardization Joint Technical Committee 21 Working Group 4 on Transparency and the International Organization for Standardization/International Electrotechnical Commission Joint Technical Committee 1/Subcommittee 42 Joint Working Group 7, contributing to the development of international standards for trustworthy and responsible Artificial Intelligence.

My current research interests include trustworthy Artificial Intelligence, explainable Artificial Intelligence, Artificial Intelligence governance, optimization algorithms for machine learning, metaheuristic optimization, uncertainty quantification, model reliability assessment, and responsible deployment of Artificial Intelligence systems. I am particularly interested in interdisciplinary collaborations that combine methodological advances in Artificial Intelligence with impactful real-world applications.