{"id":56,"date":"2019-03-26T08:07:46","date_gmt":"2019-03-26T07:07:46","guid":{"rendered":"http:\/\/www.labdma.unina.it\/?page_id=56"},"modified":"2026-05-18T09:27:19","modified_gmt":"2026-05-18T07:27:19","slug":"groups","status":"publish","type":"page","link":"https:\/\/www.labdma.unina.it\/index.php\/groups\/","title":{"rendered":"The Group"},"content":{"rendered":"\n\n\n

M.O.D.A.L. – M<\/strong>athematical mO<\/strong>delling and D<\/strong>ata A<\/strong>naL<\/strong>ysis research group<\/p>\n\n

\nIn recent years, the field of Artificial Intelligence (AI) has undergone significant advancements, reshaping how we analyze data and derive actionable insights. Our research group embraces this evolution, delving into the latest developments in Machine Learning (ML), Deep Learning (DL), and Generative AI to address complex challenges across various domains.\n\nDigital Twin technologies play an integral role in our research, allowing us to create virtual replicas of physical systems. This approach facilitates real-time simulations and predictive insights, optimizing decision-making in areas like smart cities, energy management, and autonomous systems. When combined with Generative AI, digital twins enable the simulation and anticipation of scenarios with remarkable precision, providing a nuanced understanding of complex phenomena.\n\nOur work also explores Scientific Machine Learning (SciML), blending scientific principles with modern AI techniques to enhance the interpretability and accuracy of models. This integration allows for a more profound understanding of intricate physical systems, bridging the gap between data-driven models and domain-specific knowledge.\n\nThrough these methodologies, we automate sophisticated processes\u2014from predictive analytics to real-time decision-making\u2014letting patterns and structures naturally emerge from diverse, large-scale datasets. Our expertise in mathematics, statistics, and computer science drives the development of innovative AI solutions that address the challenges of today and tomorrow.\n<\/p>\n\n

People<\/p>\n\n\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
\n \"Francesco\n\t\n \n <\/td>\n \n \"Salvatore\n\t\n \n <\/td>\n \n \"Valeria\n\n \n <\/td>\n\n <\/tr>\n

Francesco Piccialli – Founder, Head, and Scientific Coordinator of the M.O.D.A.L. group, Full Professor of Computer Science<\/p> <\/td>\n \n

Salvatore Cuomo – Co-Founder of the M.O.D.A.L. group, head and coordinator of the Scientific Machine Learning team, Full Professor of Numerical Analysis<\/p> <\/td>\n\t\n\t

Valeria Mele, member of the M.O.D.A.L. group, Associate Professor of Computer Science <\/p><\/td>\n \n <\/tr>\n \n \n\n

\"Fabio<\/td>\n \"Daniela<\/td>\n \"Stefano<\/td>\n \"Marzia<\/td>\n \n <\/tr>\n
Fabio Giampaolo<\/td>\n Daniela Annunziata<\/td>\n Stefano Izzo<\/td>\n Marzia Canzaniello<\/td>\n\n <\/tr>\n
Ph.D., Research Fellow<\/td>\n Ph.D., Research Fellow<\/td>\n Ph.D., Research Fellow<\/td>\n Ph.D., Research Fellow<\/td>\n\n <\/tr>\n
Scholar Link<\/a><\/td>\n Scholar Link<\/a><\/td>\n Scholar Link<\/a><\/td>\n Scholar Link<\/a><\/td>\n\n <\/tr>\n\n\n
\"Sara<\/td>\n \"Valentina<\/td>\n \"Anna<\/td>\n \"Lingyu<\/td>\n\n <\/tr>\n
Sara Amitrano<\/td>\n Valentina De Angelis<\/td>\n Anna Borrelli<\/td>\n Lingyu Qiu<\/td>\n\n \n \n <\/tr>\n \n
Ph.D. student<\/td>\n Ph.D. student<\/td>\n Ph.D. student<\/td>\n Ph.D. student<\/td>\n\n <\/tr>\n
Scholar Link<\/a><\/td>\n <\/a><\/td>\n <\/a><\/td>\n Scholar Link<\/a><\/td>\n\n\n <\/tr>\n \n
\"SM<\/td>\n\t\"\"<\/td>\n\t\"\"<\/td>\n\t\"\"<\/td>\n\n <\/tr>\n
SM Asiful Huda<\/td>\n Sundas Sarwar<\/td>\n Makhmoor Fiza Murk<\/td>\n <\/td>\n\n <\/tr>\n
Ph.D. student<\/td>\n Ph.D. student<\/td>\n Ph.D. student<\/td>\n <\/td>\n \n <\/tr>\n\t
Scholar Link<\/a><\/td>\n Scholar Link<\/a><\/td>\n Scholar Link<\/a><\/td>\n <\/a><\/td>\n\n\n <\/tr>\n\n \n \n<\/table>\n
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Past Ph.D. students and Research Fellows<\/p>\n\n