I am a third-year CS PhD student at UC Berkeley, advised by Emma Pierson. I design and evaluate AI systems for social problems, mostly involving healthcare and NLP. Recently, I’m excited about helping humans understand complex datasets—which increasingly underpin most of the social and natural sciences—by interpreting foundation models (arXiv 2025). Previously, I’ve worked on improving ML fairness audits (MLHC 2023), using LLMs for health equity (NEJM AI 2025), and measuring pluralistic alignment in LLMs (EMNLP 2024).
I started my PhD at Cornell Tech; I continue to collaborate with the AI, Policy, and Practice working group, and was part of the Digital Life Initiative. In 2024, I interned with the FATE group at Microsoft Research Montréal. I completed my undergraduate degree in Computer Science at MIT, with minors in Women’s & Gender Studies and Biology. I worked with the Data + Feminism Lab and the Programming Systems Group.
I occasionally write things here. I like cooking, and I occasionally write food-related things on Substack. I am grateful to all the mentors and collaborators who have helped me along the way; if I can be helpful, feel free to email me.
Selected Work
Sparse Autoencoders for Hypothesis Generation.
Rajiv Movva*, Kenny Peng*, Nikhil Garg, Jon Kleinberg, Emma Pierson.
arXiv 2025.
[working draft] [explore our demo] [code] [pip install] [bluesky]
Annotation alignment: Comparing LLM and human annotations of conversational safety.
Rajiv Movva, Pang Wei Koh, Emma Pierson.
EMNLP 2024.
[paper] [twitter]
Coarse race data conceals disparities in clinical risk score performance.
Rajiv Movva*, Divya Shanmugam*, Kaihua Hou, Priya Pathak, John Guttag, Nikhil Garg, Emma Pierson.
MLHC 2023 (Proceedings) & ML4H 2023 (Findings).
🏆 Honorable Mention, Best Findings Paper 🏆, ML4H 2023.
[paper] [twitter] [code] [Cornell news] [New York Times]
Topics, Authors, and Institutions in Large Language Model Research: Trends from 17K arXiv Papers.
Rajiv Movva*, Sidhika Balachandar*, Kenny Peng*, Gabriel Agostini*, Nikhil Garg, Emma Pierson.
NAACL 2024.
[paper] [twitter] [code] [Data Skeptic podcast]
Towards Intersectional, Feminist, Participatory ML: A Case Study in Supporting Feminicide Counterdata Collection.
Harini Suresh, Rajiv Movva, Amelia Dogan, Rahul Bhargava, Isadora Cruxên, Ángeles Martinez Cuba, Giulia Taurino, Wonyoung So, Catherine D’Ignazio.
FAccT 2022.
🏆 Best Student Paper 🏆
[paper] [twitter]
Dissecting Lottery Ticket Transformers: Structural and Behavorial Study of Sparse Neural Machine Translation.
Rajiv Movva and Jason Zhao.
BlackboxNLP @ EMNLP 2020.
🏆 Best Paper 🏆
[paper] [twitter] [slides]
Deciphering regulatory DNA sequences and noncoding genetic variants using neural network models of massively parallel reporter assays.
Rajiv Movva, Peyton Greenside, Georgi K Marinov, Surag Nair, Avanti Shrikumar, Anshul Kundaje.
PLoS ONE, 2019.
[paper] [twitter]