His research focuses on data management, emphasizing both system efficiency (e.g., scalable data platforms) and human efficiency (e.g., designing LLM-based query interfaces). His papers have been recognized as the best papers at top database conferences, including SIGMOD and VLDB. He is a fellow of the AAAS, ACM, and IEEE organizations. He has also received several teaching awards, and he is a co-founder of four startups.

TEACHING/RESEARCH STATEMENT
My research is in database management, and it is organized into two themes. The first theme focuses on designing data processing methods that work synergistically with hardware to deliver high performance to database applications. The second theme focuses on expanding the scope of data platforms, and one aspect of this theme is using a no-code approach to make data science accessible to a broad set of users.

A common aspect of my research is building actual systems to fully understand the end-to-end impact of the underlying research.