This research focuses on analyzing and predicting ship operational performance in real-world marine environments by using extensive amounts of ship operational data, including AIS data and various in-service data collected during voyages. Data-driven modeling techniques are used not only to systematically characterize the operational performance of the global fleet but also to enhance power prediction models for specific vessels by estimating various ship resistance components. Through this research, we aim to contribute to the development of a sustainable shipping industry by optimizing ship energy efficiency and reducing fuel consumption.

This research examines various green shipping technologies and strategies aimed at reducing the carbon footprint of maritime transport and evaluates their effectiveness. It supports the transition to a sustainable shipping industry through a comprehensive approach including alternative fuels, energy saving devices (air lubrication systems, wind-assisted propulsion, etc.), and voyage optimization techniques. Through this research, we aim to propose practical and feasible solutions that take into account not only technical but also environmental and economic aspects.

This research addresses the problem of biofouling on ships and optimizes hull maintenance strategies. It quantitatively evaluates the increase in hydrodynamic drag caused by marine organisms attached to the hull and analyzes the effectiveness of various antifouling strategies and hull cleaning methods. Furthermore, we aim to develop sustainable and well-balanced hull maintenance strategies by comprehensively considering operational economics, environmental impact, and social factors.

This research focuses on developing intelligent operation and navigation systems that maximize ship operational safety and efficiency by integrating Artificial Intelligence (AI) and automation technologies. It includes the research topics such as real-time ship condition monitoring, collision avoidance algorithms, seakeeping performance evaluation during voyage, economical and environmentally friendly route planning, and automated decision support functions. Through this, we aim to minimize human error and simultaneously improve the safety and efficiency of maritime operations.