Aims and mission:
The coastal and marine environments are affected by oceanic phenomena (e.g., wind, wave, current). The practical and sustainable deployment of coastal and marine operations, including shipping, marine energy, fishing, offshore exploration, and coastal infrastructure development, relies heavily on accurate and reliable ocean forecasting.
Improved forecasting capabilities are essential for the development and maintenance of marine energy operations, supporting the transition to a low-carbon economy and contributing to the attainment of the UN’s Sustainable Development Goals (SDGs).
Hence, our mission is to:
Establish a multi-disciplinary, world-leading CDT that explores the feasibility of integrating AI into ocean forecasting models for marine operations
Advance research in three key areas of Artificial Intelligence, Ocean Forecasts, and Marine Operations
Provide successful studentship projects supported by the University of Strathclyde
Develop collaboration with internal, external, and international partners
This Centre for Doctoral Training (CDT) has been funded by the University of Strathclyde in 2023.
Leadership Team:
Lecturer & Chancellor’s Fellow
Civil & Environmental Engineering
Faculty of Engineering
Expertise:
Coastal Engineering, Ocean Climate change, Wave Modelling, Numerical and Machine Learning methods, Ocean Renewable Energy
Research Group:
Lecturer & Chancellor’s Fellow
Mathematics and Statistics
Faculty of Science
Expertise:
Modelling and simulation, wave propagation, optimisation, data analytics, signal processing, ML, Bayesian inference, imaging and inverse problems
Research Group:
Waves, Inverse Problems and Imaging (WiPi)
Lecturer & Chancellor’s Fellow
Naval Architecture, Ocean & Marine Eng
Faculty of Engineering
Expertise:
Experimental mechanics, sensor and actuator technologies and offshore renewable energy
Meet the team:
Vicky Martí Barclay
Merlijn Surtel
Jack Lewis
Topic: AI-Based Approaches for Ocean Forecast and Development of Ensemble Ocean Climate Data
Bio: my background is in oceanography and marine renewable energy. Before coming to Strathclyde, I was a researcher in ocean renewable energy at Bangor University for nearly 3 years. I love being in (and on) the ocean doing water sports but out of season you’ll mostly find me in the forest doing orienteering.
Topic: Physics Informed Machine Learning for Ocean Forecasting
Bio: I'm a computer scientist interested in machine learning and the mathematics behind it. Novel techniques for machine learning particularly intrigue me.
Research Interests: Machine Learning, Bayesian Deep Learning, Explainable AI, Modelling, Algorithms
Topic: Optimisation of Offshore Wind Farm Placement and Operation Using AI and Ocean Forecasting
Bio: I have a background in marine renewable energy with a particular focus on Tidal and Wind energy and the generating forces behind them.
I have previously worked as a researcher at Bangor university using our research outputs to collaborate with industry and progress the MRE sector. I enjoy surfing, climbing and mountaineering in my free time