Hi, I’m Raj, a CS PhD student at Cornell Tech. I work on responsible AI and computational social science. Recently, I’ve been thinking about algorithmic fairness, health disparities, and language data – and especially their intersections. I am advised by Emma Pierson and supported by an NSF GRFP.
Previously, I studied CS at MIT with minors in Biology and Women’s & Gender Studies. I was lucky to work in the Data + Feminism Lab, where we developed intersectional, participatory NLP systems to support activist labor (FAccT 2022). Before that, I worked on efficiency and compression in neural networks, particularly for language models [1, 2, 3]. I am very thankful to my excellent mentors along the way, including Harini Suresh, Jonathan Frankle, and Shayne Longpre; see here for a longer list of people I am very indebted to! I was also president of AI@MIT, which taught me a lot about teaching, mentorship, and logistics.
I hew closely to PhD stereotypes: my primary hobbies are baking, rock climbing, reading, mixology, and tennis. If you’d like to read some unreliable recipes I’ve written, see here.
Updates
- [2023-08] I presented our paper on granular race disparities at MLHC 2023! Thanks for the excellent conversations; code will be up soon!
- [2023-07] New working paper on arXiv! We analyzed 14K language modeling-related papers on arXiv to detail recent publishing trends.
- [2023-04] Our new paper is on arXiv, the first from my PhD! We find that granular race categories are critical to algorithmic fairness analyses in healthcare; here’s a summary.
- [2022-08] Our paper on compressing language models is accepted to COLING 2022! I led this project during an Apple internship in 2021.