Welcome to my page! I’m a staff research scientist at OpenAI, working on data value and quality.
Before that, I was a research scientist at Google, where I led efforts to efficiently predict data value in foundation models and contributed to Gemini and Gemma. I did my PhD at MIT where I was advised by Rahul Mazumder and worked on model compression and combinatorial optimization.
My research has been recognized with best paper awards and honorable mentions from INFORMS ICS (2023), KDD (2022), INFORMS IOS (2020), INFORMS ICS (2020), MIT (2020), MIP Workshop (2019).
Some areas I’ve worked on in recent years:
Data value: designing methods to predict the impact of training data on model performance
Data quality: developing techniques to evaluate and control various aspects of data quality.
Model compression: researching fundamental techniques for pruning and feature selection.