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Società Italiana Reti Neuroniche
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Società Italiana Reti Neuroniche
Civil engineering regards many of the most fundamental aspects of everyday life in society, and despite being culturally associated with the most traditional engineering sector, it is instead undergoing radical overturning in recent periods, especially in the last decade. Continuously increasing demanding solutions are requested for civil engineer structures such as buildings, bridges, dams, tunnels, and roads, and nowadays computer-aided applications along the entire lifecycle are crucial for efficient maintenance programs, decision-making supports, design optimization for effective economic resources planning, and ensuring high safety levels. Artificial intelligence and machine learning tools are permeating all the scientific sectors, fostering emerging trends in the civil engineering field related to risk mitigation, structural health monitoring, structural optimization, automation, computer vision, hydraulic and geotechnical advancements, transportation engineering revolutions, thus projecting this traditional engineering sector toward a new sustainable, environmentally friendly, cost-effective, and topical and futuristic perspective.
However, special concerns still arise due to often lack of interpretability of complex deep learning models rather than analytical, experimental, and empirical past procedures. Therefore, researchers are called to provide deeper insights into knowledge representation and reasoning, the effectiveness of information fusion, computer vision interpretability, and artificial intelligence model optimization, while employing them in real-world civil engineering applications.
This Special Session aims to promote the latest research contributions of artificial intelligence within the civil engineering research field, thus original papers are invited to be submitted pointing out these relevant models’ interpretability aspects.
The main topics, but not limited to, are:
Giuseppe Carlo Marano, PhD in Structural Engineering at the University of Florence (2000). Post-doctoral scholarship in “Civil Engineering Science” at Technical University of Bari in 2001 and Lecturer in structural engineering in the same university in 2001. Visiting assistant professor in Cambridge (2002), associate professor in 2011 at Politecnico di Bari and visiting Professor in Loughborough (2012) and at Hunan University, Changsha, Hunan Province (China) (2014), is research fellow at the SIBERC (Sustainable and Innovative Bridge Engineering Research Center), Fuzhou University, Fuzhou, Fujian Province, China and (2016/2018) full Professor in Structural Design, Faculty of Civil Engineering, Fuzhou University, Fuzhou, Fujian Province, China. From 2018 is full professor in structural Design at Politecnico di Torino, where he also covered vice director of the Department of Structural, Environmental and Geotechnical Engineering until 2023. His research interests deal with structural optimization, form finding and structural health monitoring. He is author of four European patents and more than 300 papers published in international journals or presented at conferences.
Giansalvo Cirrincione, (Senior Member, IEEE) received the M.S. degree in electrical engineering from the Politecnico di Torino, Italy, in 1991, and the Ph.D. degree from the Laboratoire d’Informatique et Signaux de l’Institut National Polytechnique de Grenoble, Grenoble, France, in 1998. He was a Postdoctoral Scholar at the Department of Signals, Identification, System Theory
and Automation (SISTA), Leuven University, Leuven, Belgium, in 1999. Since 2000, he has been an Assistant Professor with the Department of Electrical Engineering, University of Picardie Jules Verne, Amiens, France. He is currently an Adjunct Associate Professor with The University of the South Pacific. His current research interests include neural networks, data analysis, Computer vision, brain models, and system identification.
Marco Martino Rosso, M.Sc. Degree cum laude in Structural Civil Engineering in 2020 from Technical University of Turin, Politecnico di Torino, TO, Italy, and soon in 2024 he will graduate with the Structural Engineering Ph.D. school in the Civil and Environmental Engineering program at Politecnico di Torino University, TO, Italy. His research fields cover structural dynamics and structural health monitoring methods, machine learning and deep learning, but also meta-heuristic algorithms for constrained optimization problems in structural optimization area.
Angelo Aloisio, PhD in Civil Engineering from University of L’Aquila, is Postdoc researcher at the University of L’Aquila. His research is focused on the Structural Health Monitoring, Timber Engineering and Seismic Engineering. Research activities are conducted within European and National projects. He is the author of more than 150 peer-reviewed scientific publications for international journals and conference proceedings.
Jonathan Melchiorre , he is a Ph.D. student in the national Ph.D. programme on artificial intelligence. His research focus on the application of artificial intelligence on structural engineering problems. The main topics are structural optimization, form-finding methodologies and structural geometries in general.
WIRN 2024 è parzialmente finanziato da EU NextGeneration, PNRR Mission 4 Component 2 Investment 1.1 – D.D. 1409 del 14-09-2022 PRIN 2022 – Project code “P20222MYKE” – CUP: B53D23025980001, dal titolo “A Pilot analysIs of behavioRal and opeRational data for detEcting Socio-emotional PrEcursors of mild CogniTIVE impairments (MCI) and demEntia” (IRRESPECTIVE)
