Research interests:

Machine learning
Ecosystem modeling
Population dynamics
Spatial analysis
Marine ecology
Ecological and socio-economic interactions

Key aspect of my previous post-doctoral research was the development of a dynamic model for the Gulf of Mexico to predict trends of ecosystem change in response to natural and anthropogenic scenarios.
Currently, my research investigates the effect of offshore renewables on the marine system. Specifically, ecosystem Bayesian models will be developed to assist the development of offshore devices and design to support the confident prediction of the environmental impact and provide information on the ecological benefits and trade-offs.

Career history:

Post-doctoral research scholar for the National Oceanic and Atmospheric Administration Integrated Ecosystem Assessment Program, University of Miami, Florida.

Post-doctoral research fellow for the EPSRC funded "Supergen Offshore Renewable Energy (ORE) Hub", School of Biological Sciences, University of Aberdeen.

Active research projects:

Supergen Offshore Renewable Energy (ORE) Hub. EPSRC. (2018-2022)

Sustainable Marine Ecosystems and Offshore Energy: A Bayesian modelling approach. BEIS, HartleyAnderson (2019-2023)

Recent publications:

Trifonova, N., Karnauskas, M. and Kelble, C., 2019. Predicting ecosystem components in the Gulf of Mexico and their responses to climate variability with a dynamic Bayesian network model. PloS one, 14(1), p.e0209257.

Uusitalo, L., Tomczak, M.T., Müller-Karulis, B., Putnis, I., Trifonova, N. and Tucker, A., 2018. Hidden variables in a Dynamic Bayesian Network identify ecosystem level change. Ecological Informatics, 45, pp.9-15.

Trifonova, N., Maxwell, D., Pinnegar, J., Kenny, A. and Tucker, A., 2017. Predicting ecosystem responses to changes in fisheries catch, temperature, and primary productivity with a dynamic Bayesian network model. ICES Journal of Marine Science, 74(5), pp.1334-1343.