About

I am a Principal Scientist at Snowflake, working on making Data and AI systems reliable and trustworthy. My work focuses on integrating formal methods and rigorous software testing techniques into the development process.

Previously, I was a Principal Applied Scientist at Amazon Web Services where I led a team that built tools for model checking, scalable fuzzing, property-based testing, and runtime monitoring of distributed systems. These tools were adopted by 80+ service teams and 600+ developers across AWS, finding critical bugs in flagship services including S3, DynamoDB, EBS, Aurora, EC2, and CloudFront. This work contributed to a cultural shift in software engineering practices at AWS, summarized in the ACM article Systems Correctness Practices at AWS.

I hold a PhD in Computer Science from UC Berkeley (2019), where I was co-advised by Prof. Sanjit Seshia and Dr. Shaz Qadeer. My PhD work created the P programming framework for reasoning about correctness of distributed systems, which is used across industry (AWS, Microsoft, DeepSeek) and academia.

Before graduate school, I spent 2+ years at Microsoft Research India working on scalable model checking for concurrent systems. During my time at IIT Kanpur, I led the on-board computer team for India's first nanosatellite JUGNU, which was successfully launched on 12 October 2011.