#  Aleksandra Conevska 

PhD Candidate in Government, GSAS

 

 

 



   ![Aleksandra Conevska](/sites/g/files/omnuum8171/files/styles/hwp_4_5__320x400/public/2025-12/Aleksandra-Conevska_2025.jpg?h=8c809ec5&itok=BRAKkCS_) 

 



 

 email <aleksandraconevska@g.harvard.edu> 

 laptop\_windows [Website](https://aleksandraconevska.com/) 

 laptop\_windows [GitHub](https://github.com/aconevska) 

 

- [ Twitter   ](https://x.com/aleksandracone)
- [ Linkedin   ](https://www.linkedin.com/in/aleksandra-conevska/)
 
 



 

I am a PhD candidate in the Department of Government at Harvard University. I study elections, institutions, and interest group and party behavior, particularly in the context of climate change. In my more applied work, I use computational and experimental methods to understand voter behavior and strategic campaign messaging, and to establish policy evidence relevant to the energy transition. I am also part of a group of researchers committed to digitizing [Cast Vote Record data](https://doi.org/10.1038/s41597-024-04017-1) in the United States, unlocking new research frontiers applicable to big questions in academia as well as real world campaign strategy.

I am currently a Graduate Fellow at the [Institute for Quantitative Social Science](https://www.iq.harvard.edu/about) (IQSS), the [Center for American Political Studies](https://caps.gov.harvard.edu/) (CAPS), and the [Harvard STAR Lab](https://starlab.wcfia.harvard.edu/), and a Harvard [Salata Institute](https://salatainstitute.harvard.edu/) Fellow.

Prior to Harvard, I was a Fulbright Scholar at Johns Hopkins University after earning a Bachelor of Arts and Science from McGill University with Joint Honours in Environmental Science and Political Science. I have also worked as a consultant for the World Bank Group, London Economics International, and Siemens. My research has been published in the *American Political Science Review*, *Nature Scientific Data*, *International Studies Quarterly*, and *Energy Research &amp; Social Science*.



 

 

 





 

 

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