isc36@cornell.edu
Bio
Hi! I’m Isabel, and I’m a second-year Information Science PhD student at the Cornell Bowers College of Computing and Information Science. I use data science and computational social science methods to conduct socio-technical audits of algorithmic systems, with a particular interest in understanding potential social harms. I am fortunate to be advised by Mor Naaman and Allison Koenecke.
Work Experience
Prior to joining the Cornell Info Sci PhD program, I worked for several years as a data scientist at Spotify. At Spotify, I contributed to several teams, including algorithmic impact and responsibility and ML Engagement (Lex Beattie speaks about ML Engagement here).
I graduated with a B.S. in Statistics and Data Science from Yale, where my senior thesis on the latent assumptions in word embedding debiasing methods was advised by Professors Elisa Celis and Issa Kohler-Hausmann. At Yale, I was a research assistant for projects in the STEM PERL lab and the Human Nature Lab and interned with organizations focused on education (InsideSchools) and child welfare policy research (Action Research Partners).
News
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November 2025 Working paper “Introducing AI to an Online Petition Platform Changed Outputs but not Outcomes.” now on arXiv!
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November 2025 Understanding Sensitive Attribute Association Bias in Recommendation Embedding Algorithms now out in ACM Transactions on Recommender Systems.
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November 2025 I will be giving a parallel talk "Auditing Government Ad Delivery Skew in Practice" and presenting a poster "Introducing AI to an Online Petition Platform Changed Outputs but not Outcomes" at CODE@MIT.
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October 2025 Presenting a poster "Introducing AI to an Online Petition Platform Changed Outputs but not Outcomes" at the Yale FDS Workshop: New Directions in Social Algorithms Research.
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August 2025Moving Cornell campuses to Cornell Tech on Roosevelt Island in NYC - let me know if you're in the city and want to catch up!
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May 2025Opinion piece As Government Outsources More IT, Highly Skilled In-House Technologists Are More Essential now out in Communications of the ACM.
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August 2024Excited to join the AIPP initiative!
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August 2024Moving to Ithaca to start my PhD in Information Science at Cornell University!
Publications
Most recent publications on Google Scholar.
Isabel Corpus, Eric Gilbert, Allison Koenecke, and Mor Naaman. “Introducing AI to an Online Petition Platform Changed Outputs but not Outcomes.” arXiv preprint arXiv:2511.13949 (2025). https://arxiv.org/pdf/2511.13949
Lex Beattie, Isabel Corpus, Lucy Lin, and Praveen Ravichandran. 2025. Understanding Sensitive Attribute Association Bias in Recommendation Embedding Algorithms. ACM Transactions on Recommender Systems https://doi.org/10.1145/3777548
Kumar, Navin, Isabel Corpus, Meher Hans, Nikhil Harle, Nan Yang, Curtis McDonald, Shinpei Nakamura Sakai et al. “COVID-19 vaccine perceptions in the initial phases of US vaccine roll-out: an observational study on reddit.” BMC Public Health 22, no. 1 (2022): 446. https://pubmed.ncbi.nlm.nih.gov/35255881/
CV
Contact Me
You can reach me by email at isc36@cornell.edu. I am also on LinkedIn, and as of recently, Bluesky!