Dr Neda Trifonova

Biography

Neda's research interests include ecosystem modelling; the application of machine learning techniques, such as Bayesian networks, to investigate environmental aspects of offshore renewable energy and climate change. Neda also has interest in natural capital approaches, cumulative and environmental assessments, and evaluation tools for the delivery of environmental net gain and socio-economic benefits. 

Prizes and Awards

• Scottish Universities Life Sciences Alliance (SULSA) Early Career Reseacher (ECR) Prize for the Ecosystems Theme
• British Ecological Society/NatureScot Policy Fellowship 2021-2022 

Current Research

ECOFlow/ Establishing a Framework for Quantifiable Evidence and Impact of Ecosystem Change Throughout the Lifecycle of UK Floating Offshore Wind Farms (EQUIFy) (2025-28, NERC/The Crown Estate).EQUIFy will use an array of modelling approaches, autonomous monitoring systems and decision support tools to provide a transferable evidence framework that improves current understanding of the likely future effects of FLOW, with a focus on planned developments in the Celtic Sea. I am a Co-Investigator in Work Package 5 that brings together a range of physical and biological observations and modelling outputs with established decision support tools tailored to enhance the capabilities of planners, spatial managers and industry, to access evidence guiding sustainable development of FLOW.

ECOWind/ Physics-to-Ecosystem Level Assessment of Impacts of Offshore Windfarms (PELAgIO) (2022-25, NERC/The Crown Estate). PELAgIO will support the development of evidence-based policy and marine management through interdisciplinary research that explores the consequences of offshore wind development on marine ecosystems. By observing and modelling over a large range of physical and biological scales, using a combination of autonomous platforms and ocean robots, research vessels and satellite observations, PELAgIO will build an ecosystem-level understanding of projected changes.

The Marine Energy, Biodiversity and Food Nexus (EcoNex) (2022-24, UKERC). This project will work with renewable industry and policy bodies to enable evidence-based, informed actions to improve decision making when balancing environmental, social, and economic impacts and ensuring marine net gain, as part of national policy assessments.  

Supergen Offshore Renewable Energy (ORE) Hub (2019-2022 EPSRC). The aim of the project is to bring together and stimulate synergistic adventurous research that supports and accelerates the development of offshore wind, wave and tidal technologies for society’s benefit. Neda will be using machine learning techniques such as Bayesian networks to investigate the effect of offshore renewable energy and climate change on the North Sea marine system. She also will be looking at developing evaluation tools to enable the exploration of trade-offs in a range of currencies for net gain, such that objective judgements can be made as to how to best maximise the environmental and social co-benefits, while delivering net zero. 

Past Research

• National Oceanic and Atmospheric Administration’s Integrated Ecosystem Assessment Programme for the Gulf of Mexico (2017-2019). Development of quantitative and qualitative Bayesian network models for the better understanding of population dynamics within different ecosystems.
• PhD in Computer Science from Brunel University, 2016. Development of dynamic Bayesian networks to investigate fish population dynamics throughout space and time within the North Sea and understand their interactions with fisheries and climate. The PhD was conducted in collaboration with the Centre for Environment Fisheries Aquaculture Science (UK) and the Maurice Lamontagne Institute, part of a network of Fisheries and Oceans (DFO), Canada in Mont-Joli, Quebec.

Funding and Grants

• Scottish Alliance for Geoscience, Environment and Society (SAGES) Postdoctoral and Early Career Researcher Exchange (PECRE) Award (PI)
• Scottish Universities Life Sciences Alliance (SULSA) Early Career Researcher (ECR) Prize Winner 2020 Ecosystems Theme (PI)