Surajit Chaudhuri

Surajit Chaudhuri is a Researcher at Microsoft, with a career spanning decades in database systems and data management. He has received the prestigious SIGMOD Edgar F. Codd Innovations Award (2011) for his contributions to query optimization, index tuning, and data lakes.

• Research Interests: His work focuses on database tuning, approximate query processing, fuzzy similarity joins, automated data transformations, and machine learning integration for scalable data systems.
• Recent Publications: In 2025, his research includes Auto-Test for unsupervised error detection in tables, Esc for budget-aware index tuning, and MMTU for multi-task table understanding benchmarks. Earlier works in 2024–2023 address spreadsheet formula recommendation, low-overhead index filtering, and time-series pattern recognition.
• Scientific Impact: He has co-authored influential papers in SIGMOD, VLDB, and IEEE Transactions, shaping practices in cloud databases, query optimization, and self-service BI. His collaborations span institutions like Microsoft, MIT, and ETH Zurich.