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Energy, Sustainable Finance and Machine Learning, University of Oxford

Galina is based at the Sustainable Finance Programme of the University of Oxford’s Smith School of Enterprise and the Environment. She is leading projects focusing on quantifying barriers to the global electricity sector’s transition to renewable energy and away from fossil fuels, and the associated carbon lock-in risks.

In her work, she applies machine-learning-based techniques to uncover novel insights form large complex asset-level datasets, to inform future energy infrastructure investment decisions.

Her research has culminated in impactful publications in top journals, with two of her recent Nature Energy studies covered by over 100 news outlets and radio programmes, including BBC, The Guardian, Bloomberg, The New York Times and TIME, and expert pieces in Joule and Nature Energy.

Previously at the OECD, an international organisation in Paris, she led projects for the public and private sector on the decarbonisation of the extractive industry, climate finance and natural capital management. A highlight of Galina’s career also includes her work as a direct economic adviser to the Minister of Industrialisation and Trade in Namibia.

Galina holds an MPhil in spatial economics and urban planning from the University of Cambridge and MA in economics from the University of Glasgow.


  • –present
    PhD Candidate, Energy, Sustainable Finance, Data Science and Machine Learning, University of Oxford


    University of Oxford, DPhil
    University of Cambridge, MPhil


  • 2021
    Alova, G., Trotter, P.A. & Money, A. A machine-learning approach to predicting Africa’s electricity mix based on planned power plants and their chances of success. Nat Energy 6, 158–166 (2021)., Nature Energy
  • 2021
    Alova, G. and Caldecott, B. A machine learning model to investigate factors contributing to the energy transition of utility and independent power producer sectors internationally, iScience (2021),, iScience
  • 2020
    Alova, G. A global analysis of the progress and failure of electric utilities to adapt their portfolios of power-generation assets to the energy transition. Nat Energy 5, 920–927 (2020)., Nature Energy