About me

I’m a fifth-year Computer Science PhD student at Stanford, advised by Prof. Chris Re and affiliated with the Stanford AI Lab, Statistical Machine Learning Group and Center for Research on Foundation Models (CRFM).

I’m interested in sequence modeling techniques for building large-scale foundation models, as well as problems that arise due to the deployment of ML models to practice. These days I’m also thinking about how the application of FMs will change computing interfaces in the coming decades, especially in fields that require deep, exploratory work like data science.

During my PhD I’ve worked on methods for model auditing (Robustness Gym, Mandoline) and model robustness (Model Patching), interactive data systems for machine learning (Meerkat), new primitives for sequence modeling (S4), as well as applications of sequence models to audio generation (SaShiMi), image and video classification (S4ND), time-series forecasting and medical applications (GERD Diagnosis). I was fortunate to be an early team member in the Stanford Mercury project, which has since grown into the Center of Research for Foundation Models (CRFM). I’ve also done a bunch of work on bringing Data-Centric AI into the public eye, through a GitHub repo (800+ stars), as well as by organizing two widely attended Data-Centric AI workshops to help bring people from the area together (one with James Zou and Stanford HAI, the other with the Snorkel AI team, which is now a yearly event).

I’m also proud of our work (alongside Dan, Piero, Fiodar) on building the Stanford MLSys Seminar series from zero to 10K subscribers on YouTube over 1.5 years, and offering it as a class at Stanford for a year! I’m always interested in creating high-quality content, so ping me if you have ideas.

I’ve been fortunate to have been advised by brilliant mentors past and present, among them Prof. Emma Brunskill, Prof. Fei-Fei Li, Prof. Jure Leskovec and Dr. Sidhartha Sinha at Stanford, Prof. Aditya Parameswaran and Prof. Hari Sundaram at UIUC and Prof. Mausam at IIT-Delhi. I’m grateful to them for their advice and support through the years.

Prior to my time at Stanford, I graduated with a Master’s degree from the Department of Machine Learning at Carnegie Mellon University in 2018, where I was a recipient of the Siebel Scholarship in 2018. In my undergrad, I majored in Electrical Engineering at the Indian Institute of Technology - Delhi (IITD).

In my spare time, I enjoy learning pottery (I’m still a beginner), watching e-sports (Valorant) and reading shitposts on Twitter.