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Polygence Scholar2023
Subha Vadlamannati's profile

Subha Vadlamannati

Mercer Island High SchoolClass of 2024Mercer Island, Washington


Hi guys! I am a sophomore at Mercer Island High School and I am interested in the fields of data science, mathematics, computational linguistics, and machine learning. I also love volunteering and I have my own registered non-profit organization, Linguistics Justice League. In my free time, I learn and converse in Arabic, practice the piano, and read.


  • "Producing Mind Maps by Clustering Language Model Embeddings" with mentor Efthimios (Mar. 15, 2023)
  • "The Gender Disparity of Refugee Earnings in the U.S." with mentor Holly (Aug. 4, 2021)

Subha's Symposium Presentation

Project Portfolio

Producing Mind Maps by Clustering Language Model Embeddings

Started Jan. 12, 2023

Abstract or project description

Mind maps are a visual way to understand how concepts are related to each other. They are usually produced my a domain expert, and consist of concepts as bubbles which are connected to others in a kind of web. Centrally important concepts are closer to the middle and connected to more concepts. We plan to use language models that can take words / phrases as input and then output vectors that can be clustered together to produce mind maps. We would like to investigate whether the mind maps which are produced by these clusterings are similar to those produced by a domain expert.

Project Portfolio

The Gender Disparity of Refugee Earnings in the U.S.

Started Dec. 29, 2020

Abstract or project description

The refugee crisis impacts both low and high-income countries alike, and the question of refugee assimilation receives much attention worldwide. While all refugees face various challenges in assimilating to their host countries, female refugees face additional challenges. This paper focuses on the earnings of refugees upon arrival to their host countries. The 2018 Annual Survey of Refugees was used to study the earnings trajectory of male and female refugees who arrive in the United States. Results reveal a significant earnings gap of approximately $1.70 an hour, which is equivalent in pay to male refugees receiving almost eight more years of schooling. To examine the underlying mechanism behind this result, this paper studies how the predicted earnings trajectory varies when including the UNDP Human Development Index and the World Economic Forum Global Gender Gap variable, using refugees’ country of birth. Findings indicate robust results that female refugees do not benefit from increases in human development, while both male and female refugees benefit from increases in gender equality. These results have important implications for refugee policy in the form of cash assistance or vocational training.