Hi, I'm Noah.
I'm a fourth-year PhD candidate and the Carl J. Friedrich Fellow in the Department of Government at Harvard
University, where I also received my MA (2024) and BA (2022). In the Summer of 2025, I was a Quantitative Research
Intern at Two Sigma, where I continue to work part-time during the academic year.
My research studies the origins, structure, and persistence of political cleavages, particularly from a
comparative and geographic
perspective. I also work on computational methods for large-scale data collection, including the use of language
models for historical document digitization, record linkage, and ethnicity inference.
I am the creator of the Small-Area Global Elections (SAGE) Dataset, a database of geocoded,
small-area (usually polling-station level) election results for 110 countries. You can read more, download the
data, and explore it on the map here.
You can access EnsembleLink, my state-of-the-art method for zero-shot record linkage, here.
At Harvard, I have twice taught the Ph.D.-level "Math Prefresher" and GOV 2020: The Hidden Curriculum (for Gary
King). I have also taught STAT 186: Causal Inference (for Susan Murphy) and GOV 97: Political Geography
(instructor on record), as well as a GIS workshop for PhD students. Separately, I have also done redistricting
consulting.
You can contact me by email at noahdasanaike@g.harvard.edu.
Posts
Research
Publications
Working Papers
Substantive
- The Structure of Technological Revolutions: What the Last Structural Transformation Tells Us About the Next
One (with Torben Iversen)
- Persistence Without Program: Family Transmission Among Nazi-Émigré Descendants [working
paper]
- Local Absorption and the Political Consequences of Structural Transformation [working
paper]
Methodological
- Probabilistic Race and Ethnicity Prediction Using Group-Specific Name Lists (with Kosuke Imai
and Kyla Chasalow)
- Using Embedding Models to Improve Probabilistic Race Prediction (with Kosuke Imai) [working
paper]
- Zero-Shot Digitization of Historical Documents with Vision Language Models [working
paper]
- Pre-Trained Language Models as Zero-Shot Tools for Social Science Research [working
paper] [EnsembleLink] revise
and resubmit
- Going Glocal: A Macro-Micro Approach to Political Science (with John Gerring) [working
paper]
Additional Work
- Dasanaike, Noah and Grzegorz Ekiert. (2025). Autorytarne Preferencje Wyborców Jako Przyczyna Erozji
Demokracji. Almanach 2025/2026, Concilium Civitas. [article pdf]
- Ekiert, Grzegorz and Noah Dasanaike. (2024). The Return of Dictatorship. Journal of
Democracy. [article pdf], [publication page], [working
paper], [interview]
- Dasanaike, Noah. (2021). Businessperson Deputies and Party Cohesion: Evidence from the Russian State
Duma. Party Politics. [article pdf]