Proceedings of the 4th International Conference on Modelling and Optimisation of Ship Energy Systems
Authors
Andrea Coraddu (ed)
Department of Maritime and Transport Technology, Faculty of Mechanical Engineering, Delft University of Technology, The Netherlands
https://orcid.org/0000-0001-8891-4963
Keywords:
Alternative Fuels, Efficiency, Systems Optimization, Modeling and Control, Data Driven Methods, Ship Design, System Integration, Efficiency Optimization, Emissions Reduction
Synopsis
MOSES 2023 has continually served as an influential platform, fostering innovation and discussions shaping maritime energy systems’ future. Last year’s conference expanded its scope to include topics reflecting the latest technological advances impacting our industry. Key discussions focused on reducing fuel consumption, minimizing environmental impacts, and optimizing lifecycle costs in ship design and operations amidst stringent regulations and fluctuating market conditions. MOSES 2023 provided a vibrant forum for sharing innovative research, practices, and policies, and the proceedings encompass contributions from academics, industry experts, and emerging researchers, spanning diverse topics such as system modelling, optimization, control, and environmental sustainability. Highlights from the conference included a new roundtable on Data and Digitalisation, which brought together leading figures from industry and academia to explore the integration of IoT, AI, and blockchain technologies in maritime operations. This discussion focused on challenges related to data privacy, integration, and cybersecurity, underpinning the strategic importance of digital technologies in enhancing operational efficiency and safety. We invite scholars, professionals, and enthusiasts in ship energy systems to explore these proceedings, encapsulating the insights and discussions from MOSES 2023.
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Author Biographies
Andrea Coraddu (ed), Department of Maritime and Transport Technology, Faculty of Mechanical Engineering, Delft University of Technology, The Netherlands
Dr Andrea Coraddu is an Associate Professor at Delft University of Technology (TU Delft) in the Department of Maritime and Transport Technology. Previously, he held the position of Associate Professor in the Department of Naval Architecture, Ocean & Marine Engineering at the University of Strathclyde from 2 October 2020. His professional and academic trajectory includes serving as an Assistant Professor at the University of Strathclyde and a Research Associate at the School of Marine Science and Technology at Newcastle University. Further bolstering his industry expertise, Dr Coraddu served as a Research Engineer within the DAMEN R&D department based in Singapore. His role involved innovative work in the field of predictive and prescriptive analytics for maritime applications. His academic journey began at the University of Genoa, where he was awarded both a Laurea and a PhD in Naval Architecture and Marine Engineering.
Luca Oneto (ed), Department of Informatics, Bioengineering, Robotics and Systems Engineering, Università degli Studi di Genova, Italy
Luca Oneto was born in Rapallo, Italy, in 1986. He received his BSc and MSc in Electronic Engineering at the University of Genoa, Italy, respectively in 2008 and 2010. In 2014, he received his PhD from the same university in the School of Sciences and Technologies for Knowledge and Information Retrieval, with the thesis "Learning Based On Empirical Data". In 2017, he obtained the Italian National Scientific Qualification for the role of Associate Professor in Computer Engineering, and in 2018, he obtained the one in Computer Science. He worked as an Assistant Professor in Computer Engineering at the University of Genoa from 2016 to 2019. In 2018 he was co-funder of the spin-off ZenaByte s.r.l. In 2019, he obtained the Italian National Scientific Qualification for the role of Full Professor in Computer Science and Computer Engineering. In 2019, he became an Associate Professor in Computer Science at the University of Pisa and is currently an Associate Professor in Computer Engineering at the University of Genoa. He has been involved in several H2020 projects (S2RJU, ICT, DS), and he has been awarded the Amazon AWS Machine Learning and Somalvico (best Italian young AI researcher) Awards. His first main research topic is the Statistical Learning Theory, with particular focus on the theoretical aspects of the problems of (Semi) Supervised Model Selection and Error Estimation. His second main topic of research is Data Science, with particular reference to the problem of Trustworthy AI and the solution to real-world problems by exploiting and improving the most recent Learning Algorithms and Theoretical Results in the fields of Machine Learning and Data Mining.
Published
August 22, 2024
Copyright (c) 2024 Andrea Coraddu (ed), Luca Oneto (ed)
