Projects

Maritime Data Analysis

Post-processing of emission and fuel consumption (includes PoC application)

Change Detection in Dynamic Shallow Areas

Investigate dynamic shallow-water areas (e.g., fjord outlets) using satellite data and remote-sensing techniques and identify and quantify changes over time.

Deep Learning

Deep Learning, either in:

- Feature detection (Rocks in Greenland, coastline delineation, etc.)

- Satelite-derived bathymetry

- Automated cleaning of CSB data

Foundation Models for Forecasting Water Time Series

Reservoir detection using deep learning approaches

Refinement of flow accumulation raster using information from water surface frequency and digital elevation models

Estimation of reservoir volume beneath recorded DEM using ML or geostatistical approaches

Downscaling AI weather models to local areas

Sensor-agnostic coastline delineation using foundational models

Time Series Forecasting for Water Applications Using N-HiTS

Super-Resolution for Groundwater Models Using Multi-Resolution MIKE SHE Grids

Multi-Resolution Modeling for Flexible Mesh Coastal-Ocean Models

Koopman Autoencoders as surrogates for MIKE 21 coastal models with integration of observed data

Neural Operators as Surrogates for Coastal Ocean Modeling with MIKE 21 HD

GNN-Autoencoders as Surrogates for Coastal Ocean Modeling with MIKE 21 HD

Self-Supervised Deep Learning in Remote Sensing for Wetland Classification based on Satellite Time Series

LIDAR-corrected Digital Terrain Model for Hydrological Applications using Deep Learning

A Hull Inspector Platform

Development of Hulinspector platform to digitize data from diving companies and onboard crews conducting GoPro/ROV hull inspections

Simulation of liner shipping network execution

Heuristics for Terminal friendly Liner Shipping Network Designs

Inspection Prediction

Development of a risk indication for successful inspection based on the vessels condition, people onboard, and location.

Technical Fault-finding Assistant

A Fault-finding assistant that helps identify problems with mechanical and electrical equipment onboard

A Smart Model for Crew Planning

Planning crew member relief is as complex as it is changing.

It is currently done in Excel.

Ship particulars and parameters prediction tool - Based on a machine learning approach.

The interest is to develop a functional and user-friendly tool that can predict ranges of parameters and particulars of a ship, such as main dimensions, tonnage, tanks capacities, cargo capacities and more. All of these depend on the type of vessel of interest (ferries, cruise ships, work boats, etc.) With the purpose of facilitating the initial spiral design process of the conceptualization of a vessel. To achieve this goal, it will be necessary to first work out a database from which the tool can be trained continuously, so the predicted values are inside an acceptable range and category.

Cargo flow and operation tool - Based on a machine learning approach.

Ro-Ro and Ro-Pax vessels perform a daily operation of onboarding and outboarding wheel cargo for their transportation. This daily operation requires to be properly carried out, to distribute the inner loads in the correct way. However, this process can become cumbersome and in case it gets delayed, the idle time of the ship at port can be easily translated into fuel consumption for both being at shore and due to the need to compensate for wasted time (acceleration during the voyage).

Given this problem, it is of interest to develop a tool or model that can simulate loading scenarios to carry the most proper distribution. This model should be robust enough to be able to consider different cargo types, dimensions, weight distribution and deck arrangement.

A 3D BIM-Enabled Workflow for Ship Outfitting Design

The outfitting of ships—covering machinery, deck equipment, and interior furnishing—requires complex design processes where multiple disciplines must coordinate across geometry, weight, and functional requirements. Traditionally, ship designers rely on disconnected tools for structural modeling, equipment arrangement, and reporting, leading to inefficiencies and data inconsistencies. This thesis proposes the design and implementation of a prototype system that leverages Building Information Modeling (BIM) principles to create an integrated 3D workflow for the first steps of a Digital Twin.

Biofouling Pressure Model

Hull fouling causes speedloss and increase fuel consumption, posing a significant challenge to vessel efficiency.

A biofouling pressure model can help improve this.