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Marine Alliance for Science and Technology for Scotland

Marine Artificial Intelligence Forum

Welcome to the MASTS Marine Artificial Intelligence Forum
This Forum provides a platform for knowledge exchange (information, education, networking), enabling the MASTS community to benefit from and contribute to advanced AI-predicated solutions that specifically target complex problems within the marine environment. This includes the application of state-of-the-art AI techniques to existing research and the creation of synergies with other stakeholders and centres of excellence.
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Background & Objectives

Techniques grouped under the umbrella term of Artificial Intelligence (AI) are being applied across various fields of human activity, with their applications successfully tackling real-life challenges. Evidence of this is seen in the presence of approaches such as, search and optimisation, statistical learning, probabilistic modelling, and uncertain reasoning, which are increasingly used in web search engines, image and speech recognition modules, recommender systems, route planners, automated timetabling / rostering engines, etc. The marine environment is no exception to this, as state-of-the-art AI developments are already having transformational effects in several sectors – for example, environmental monitoring, logistics, resource management, planning and governance.

However, marine scientists might not be in a position to fully benefit from the potential of AI solutions as: they might be unaware of AI techniques specialised in tackling their type of problem / data; they might achieve sub-optimal results when applying/fine-tuning a complex AI solution; or they might struggle to find the right collaborators to work on AI tasks (e.g., given high-demand from other non-marine sectors). This is especially problematic as promising new technologies in marine research and industry produce large amounts of data (images, videos, signals) which either require AI processing or would benefit from it – e.g.: oceanographic data from gliders, high throughput sequencing and eDNA sequencing, active acoustics for biomass and abundance estimation, automated image/video monitoring.

  • Providing a forum to facilitate networking and knowledge exchange on AI-related topics that will drive benefits to the marine environment.
  • Expanding awareness among the marine research and industry community in the potential to apply AI to existing research, and either educating these new AI users in the how or providing links to collaborators who possess the expertise. 
  • Creating synergies with other stakeholders and centres of excellence that are focusing on using AI to tackle (global) marine environmental and economic challenges in the context of climate change and energy transition.
  • Supporting the MASTS community (especially PhD students) to use relevant state-of-the-art AI techniques that can advance and enhance their work.
A Brown Crab in on the sea floor
Forum Activities

2023: Official creation of the MASTS Marine Artificial Intelligence Forum

Driven by members of the MASTS community, a proposal for the creation of a new Research Forum on Marine Artificial Intelligence was submitted and accepted.

The community is excited about this new addition to the MASTS science landscape and welcomes the newly appointed Steering Group. The Forum will participate at this year’s MASTS Annual Science Meeting with a Special Session on Artificial Intelligence.

2022: MASTS Annual Science Meeting (ASM) Special Session on “AI”

  • Prof. Jinchang Ren and Dr Yijun Yan (National Subsea Centre) “Multimodal Image Analysis for Condition Monitoring of the Ocean: from Remote Sensing to Onsite Inspection”
  • Thomas Wilding (SAMS) “From data to decisions: innovations to support the Blue Economy Vision”

Ciprian Zavoianu
– Robert Gordon University

National Subsea Centre | School of Computing | Net Zero Marine Operations Research Programme Lead | Computational Intelligence (CI) Research Group

Interests: Evolutionary computation algorithms | Combining simulation, optimization and data-driven modelling | Multi-objective evolutionary algorithms used for solving computationally intensive optimization problems

Stewart Massie
– Robert Gordon University

School of Computing | Reader with the Artificial Intelligence and Reasoning (AIR) Research Group | Theme Co-Lead Scottish Informatics & Computer Science Alliance (SICSA) Data Science Research Theme

Interests: Machine learning, information retrieval and data mining technologies | Applied solutions for text, multi-media applications and sensor networks

Tom Wilding

Senior Lecturer in Benthic Ecology and Statistical Modelling | ScotMER Benthic Receptor Group | Former Convenor MASTS Oil & Gas Environmental Research Forum

Interests: Development of novel imaging and eDNA-based approaches to monitoring change, challenging current monitoring and assessment approaches | Interface between research, policy, and regulation | Aquaculture, oil and gas decommissioning and marine renewables

Steering Group

Andrew Sweetman (Heriot-Watt University), Bingzhang Chen (University of Strathclyde), Dafne Eerkes-Medrano (Marine Directorate), Denise Risch (SAMS), Eleanor MacLeod (RGU), Ian Stewart (Heriot-Watt University), Jens Rasmussen (Marine Directorate), Jinchang Ren (Robert Gordon University, National Subsea Centre), John Halpin (SAMS), Jon Chamberlain (University of Essex), Kelly James (NatureScot), Laurence De Clippele (University of Glasgow), Lewis Drysdale (SAMS), Marion Harrald (SEPA), Neda Trifonova (University of Aberdeen), Nicolas Pugeault (University of Glasgow) and Tom Morgan (SAMS).

Member Logos Marine Artificial Intelligence Forum
MASTS Resources

We’re working behind the scenes to bring you a suite of useful, and updateable, resources including: 

  • Find an expert
  • Find facilities & equipment
  • MASTS Publications


If you would like to be updated when the resources section is live please let us know.