Bio

Hi, my name is Vicky and I am a graduate student at Stanford studying energy science and engineering. At Stanford, I worked in the INES research group, focused primarily on creating a capacity expansion model with improved spatial, temporal, and geographical resolution.

I am passionate about capacity expansion and transmission planning, power markets, utility rate structure, load forecasting, microgrids and more. I am also curious to explore the ways in which we will harness DERs and technological tools at our fingertips to create more resilient communities and energy systems. This can have broad implications for developing regions and more generally energy scarce areas.

Outside of school, you will find me running, climbing, backpacking, skiing, etc. I like everything outdoors, have an affinity for art/music, and love to salsa too. Please message me with questions or just to connect!

Honors & Awards

  • Regents' and Chancellor's Award, UC Berkeley (2020-2024)

Education & Certifications

  • Bachelor of Science, UC Berkeley, Economics, Data Science (2024)

Contact

  • Academic
    vdinov@stanford.edu
    University - Student Department: Department of Energy Science and Engineering Position: Graduate

Additional Info

Links

All Publications

  • Environmental Kuznets Curve applications for water pollution in the EU. Journal of environmental management Dinov, V., Henao, J. P., Sala, P., Vrachioli, M. 2025; 398: 127942

    Abstract

    Understanding the relationship between economic activity and water quality is critical for addressing the challenges posed by climate change. This study investigates the Environmental Kuznets Curve (EKC) hypothesis for water pollution using an unbalanced panel of eighteen European Union (EU) countries from 2000 to 2021. We estimate the effects of sectoral GDP on biological oxygen demand (BOD) to quantify the contributions of five goods-producing sectors to water pollution. To capture the role of water availability, we classify countries according to a binary water stress indicator, allowing separate analyses for water-stressed and non-water-stressed contexts. The empirical results provide heterogeneous evidence of an EKC across countries in all sectors. Specifically, the water-stressed countries exhibit monotonically decreasing relationships between sector GDP and water pollution. The non-water-stressed countries exhibit more varied results, with the manufacturing and industry sectors presenting an EKC while the agricultural sector provides evidence for a monotonically increasing relationship with water pollution. The models exhibit strong explanatory power, with high adjusted R2 values and high statistical significance across coefficients. These findings suggest that sectoral responses to water stress significantly influence the relationship between GDP and water pollution in the EU. This highlights the importance of targeted policy interventions and environmental regulations to improve water quality across the EU.

    View details for DOI 10.1016/j.jenvman.2025.127942

    View details for PubMedID 41447939

https://orcid.org/0009-0000-9780-212X