Kyla Chasalow

Kyla Chasalow

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A list of all the posts and pages found on the site. For you robots out there, there is an XML version available for digesting as well.

Pages

Posts

Future Blog Post

less than 1 minute read

Published:

This post will show up by default. To disable scheduling of future posts, edit config.yml and set future: false.

Blog Post number 4

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 3

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 2

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 1

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

portfolio

publications

Algorithms and Decision-Making in the Public Sector

Published in Annual Review of Law and Social Science, 2021

This paper surveys how algorithms are used in public sector decision-making and explores the social implications.

Recommended citation: Karen Levy, Kyla E. Chasalow, and Sarah Riley. (2021). "Algorithms and Decision-Making in the Public Sector." Annual Review of Law and Social Science, 17(1), 309–334. https://doi.org/10.1146/annurev-lawsocsci-041221-023808
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Representativeness in Statistics, Politics, and Machine Learning

Published in ACM Conference on Fairness, Accountability, and Transparency, 2021

An exploration of the concept of representativeness.

Recommended citation: Kyla Chasalow and Karen Levy. 2021. Representativeness in Statistics, Politics, and Machine Learning. In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (FAccT '21). Association for Computing Machinery, New York, NY, USA, 77–89. https://doi.org/10.1145/3442188.3445872
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Missing Data Multiple Imputation for Tabular Q-Learning in Online RL

Published in arXiv, 2025

This is an unpublished working paper that originated in Skyler Wu and my project for Professor Susan Murphy’s Reinforcement Learning class at Harvard. We would like to further develop it.

Recommended citation: Chasalow, Kyla, Skyler Wu, and Susan Murphy. 2025. Missing Data Multiple Imputation for Tabular Q-Learning in Online RL. arXiv preprint arXiv:2510.10709.
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Improving Minority Population Sampling with BISG Probabilities: Evidence from a Survey of Jewish Americans

Published in arXiv, 2026

This paper proposes a method to improve minority population sampling by integrating surname- and geography-based BISG probabilities into a Poisson sampling design and demonstrates its effectiveness in a survey of Jewish Americans.

Recommended citation: Chasalow, Kyla, Eitan Hersh, Kosuke Imai, and Laura Royden. 2026. Improving Minority Population Sampling with BISG Probabilities: Evidence from a Survey of Jewish Americans. arXiv preprint arXiv:2605.05384.
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talks

teaching

Stat 286: Causal Inference with Applications

Graduate Course, Teaching Assistant, Harvard University, Department of Statistics, 2023

Instructor: Kosuke Imai. You can find the course notes I wrote for the course here. I occasionally update these when I learn new things or have new insights on how to explain some of the topics covered.