Mathematical mOdelling and Data AnaLysis is a team of researchers and professors of DMA (Dept. of Mathematics and Applications “R. Caccioppoli”), at University of Naples Federico II. 

Our primary goal is to coordinate and enhance research, education, and collaboration, focusing on developing advanced methodologies that address complex real-world challenges. We strive to create scalable mathematical models and sophisticated data analytics methods that integrate seamlessly with diverse applications, from predictive analytics and data mining to AI-powered solutions and IoT services.

The main activities of the laboratory include:

• Research and Innovation Projects: We conduct cutting-edge research aimed at creating novel models and methods for scalable mathematical applications, deep learning architectures, inferential approaches, and complex data analysis. Our recent publications span a variety of fields, including the development of predictive models for energy consumption, the integration of Digital Twin technologies in urban mobility, and advancements in Federated Learning for distributed data analysis.
• Consulting and Strategic Assessment: We offer specialized consulting services for organizations and companies, helping them integrate advanced AI and machine learning methodologies. Our focus is on enhancing performance, improving predictive capabilities, and implementing industry best practices to drive innovation in sectors like energy management, smart cities, and industrial automation.
• Education and Training: We are committed to educating and training students, young researchers, and professionals in mathematical modeling, AI, machine and deep learning. Through workshops, seminars, and tailored courses, we aim to equip the next generation with the skills needed to tackle complex analytical challenges and excel in the evolving landscape of AI and data-driven research.

By blending rigorous mathematical principles with state-of-the-art AI techniques, M.O.D.A.L. seeks to push the boundaries of what is possible, contributing to both academic knowledge and practical applications. Our work is characterized by a strong emphasis on collaboration and the continuous pursuit of excellence, with the aim of shaping a future where innovative AI solutions meet real-world needs.