Scuola Superiore Sant’Anna (SSSA) is an autonomous, special statute public university operating in the field of applied sciences with the aims of promoting the development of culture, scientific and technological research, and innovation.
SSSA participates to AgiFlex through the centre of ICT for Complex Industrial Systems and Processes (ICT-COISP) of the Telecommunications, Computer Engineering, and Photonics Institute (TeCIP). Since its origin, this team coordinated by Dr. Eng. Valentina Colla focuses its activity in the steel sector, by investigating the application of Artificial Intelligence (AI) and advanced modelling system for the monitoring, management, optimization, and control of processes for steel production as well as steel products quality monitoring, enhancement, and optimization across the whole process chain. Since 2000 the ICT-COISP team participated to 83 EU funded projects.
ICT-COISP holds relevant skills and expertise related to development of data processing tools (e.g. data filtering, outlier detection, data classification and clustering, variable selection and features extraction, image processing), design and software implementation of Machine Learning (ML)-based models and algorithms and decision support tools for industrial applications, modelling and simulations through dedicated software tools and environments.
SSSA contributes to all WPs with a very relevant role in the development of digital twins for production and energy management. Moreover, SSSA leads the assessment of social impact and gender neutrality of the developed solution. Furthermore, as an academic institution, SSSA is deeply committed to dissemination activities, by organizing and participating to workshops, conferences and lectures related to the project topics as well as through the publication of scientific papers. Therefore, within AgiFlex SSSA also leads WP6, which is devoted to dissemination, and communication.
People
Prof. Valentina Colla, professor in Metallurgy, works at SSSA since 1998, where She established and currently coordinated the ICT-COISP research team. Her research interests comprise modelling, simulation and monitoring and control systems for application in steel industry. She is author and co-author of more than 400 scientific publications. She is an active member of the European Steel Technology Platform, where She chairs the Focus Group “Smart Factory” and co-chairs the Focus Group “Circular Economy”.
Dr. Ismael Matino holds an MSc in Chemical Engineering and a PhD in Emerging Digital Technology. He is currently assistant professor in metallurgy at the TeCIP Institute of SSSA. His research activity focuses on modelling, simulation and optimization of steelmaking processes, by using standard and advanced approaches also based on AI. He has been involved in about 20 EU-funded projects and He is an active member of the European Steel Technology Platform, in the Focus Groups “Low Carbon and Energy Efficiency” and “Circular Economy.”
Dr. Stefano Dettori is a researcher at TeCIP Institute of SSSA since 2014. His main research focuses on AI-supported time series forecasting, model predictive control, simulation and optimization of industrial processes, and decision support systems. He holds a PhD in Emerging Digital Technologies. He authored over 50 scientific publications in international journals and conference proceedings, contributing to applied AI solutions for complex industrial systems and processes.
Dr. Tommaso Grossi, Assistant Professor at Scuola Superiore Sant’Anna since 2025, focuses his research on the reliability of structural steels under future energy scenarios, particularly hydrogen and natural gas combustion. He develops machine learning strategies to accelerate multi-parametric simulations for redesigning mechanical components. Previously, he worked as an R&D engineer in Formula 1 and the automotive industry, and he holds a PhD in Industrial Engineering.
Dr. Luca Pedrelli received his PhD in Computer Science from the University of Pisa, Italy, and currently is a Research Fellow at TeCIP Institute of SSSA. He works on efficient AI for sustainable industrial applications. His research spans efficient deep learning, Reservoir Computing, graph machine learning, bioinformatics, and time-series analysis, including AI methods for healthcare, speech processing, genomics, and industrial systems; he introduced the Deep Echo State Network (DeepESN) and contributed to the development of the DeepESN and ReservoirPy libraries.
Lorenzo Vannini holds an MSc in Robotics and Automation Engineering and is currently PhD student in Artificial Intelligence, specializing in reinforcement learning and autonomous systems. MSc. Eng. Vannini joined SSSA in 2022 and is experienced in developing AI and control solutions for robotics, industrial energy optimization, autonomous driving and forecasting. He developed AI-based modelling and control solutions in international research projects and industrial collaborations.