Data-centric Dynamic Partial Order Reduction. - Krishnendu Chatterjee; Andreas Pavlogiannis; Nishant Sinha; Kapil Vaidya (CoRR, 2016)

Data-centric dynamic partial order reduction. - Marek Chalupa; Krishnendu Chatterjee; Andreas Pavlogiannis; Nishant Sinha; Kapil Vaidya (Proc. ACM Program. Lang., 2018)

The Case for a Learned Sorting Algorithm. - Ani Kristo; Kapil Vaidya; Ugur Çetintemel; Sanchit Misra; Tim Kraska (SIGMOD Conference, 2020)

Partitioned Learned Bloom Filter. - Kapil Vaidya; Eric Knorr; Tim Kraska; Michael Mitzenmacher (CoRR, 2020)

Partitioned Learned Bloom Filters. - Kapil Vaidya; Eric Knorr; Michael Mitzenmacher; Tim Kraska (ICLR, 2021)

When Are Learned Models Better Than Hash Functions? - Ibrahim Sabek; Kapil Vaidya; Dominik Horn; Andreas Kipf; Tim Kraska (CoRR, 2021)

Defeating duplicates: A re-design of the LearnedSort algorithm. - Ani Kristo; Kapil Vaidya; Tim Kraska (CoRR, 2021)

Bounding the Last Mile: Efficient Learned String Indexing. - Benjamin Spector; Andreas Kipf; Kapil Vaidya; Chi Wang 001; Umar Farooq Minhas; Tim Kraska (CoRR, 2021)

Leveraging Query Logs and Machine Learning for Parametric Query Optimization. - Kapil Vaidya; Anshuman Dutt; Vivek R. Narasayya; Surajit Chaudhuri (Proc. VLDB Endow., 2021)

SageDB: An Instance-Optimized Data Analytics System. - Jialin Ding 001; Ryan Marcus; Andreas Kipf; Vikram Nathan; Aniruddha Nrusimha; Kapil Vaidya; Alexander van Renen; Tim Kraska (Proc. VLDB Endow., 2022)

Can Learned Models Replace Hash Functions? - Ibrahim Sabek; Kapil Vaidya; Dominik Horn; Andreas Kipf; Michael Mitzenmacher; Tim Kraska (Proc. VLDB Endow., 2022)

SNARF: A Learning-Enhanced Range Filter. - Kapil Vaidya; Tim Kraska; Subarna Chatterjee; Eric R. Knorr; Michael Mitzenmacher; Stratos Idreos (Proc. VLDB Endow., 2022)

Instance-Optimized Data Structures for Membership Queries - Kapil Vaidya (2023)

Panda: Performance Debugging for Databases using LLM Agents. - Vikramank Y. Singh; Kapil Vaidya; Vinayshekhar Bannihatti Kumar; Sopan Khosla; Balakrishnan Narayanaswamy; Rashmi Gangadharaiah; Tim Kraska (CIDR, 2024)

Vista: Machine Learning based Database Performance Troubleshooting Framework in Amazon RDS. - Vikramank Y. Singh; Zhao Song 001; Balakrishnan (Murali) Narayanaswamy; Kapil Eknath Vaidya; Tim Kraska (SoCC, 2024)

Why TPC Is Not Enough: An Analysis of the Amazon Redshift Fleet. - Alexander van Renen; Dominik Horn; Pascal Pfeil; Kapil Vaidya; Wenjian Dong; Murali Narayanaswamy; Zhengchun Liu; Gaurav Saxena; Andreas Kipf; Tim Kraska (Proc. VLDB Endow., 2024)

Utilizing Past User Feedback for More Accurate Text-to-SQL. - Matthias Urban; Jialin Ding 001; David Kernert; Kapil Vaidya; Tim Kraska (HILDA@SIGMOD, 2025)

ODIN: A NL2SQL Recommender to Handle Schema Ambiguity. - Kapil Vaidya; Abishek Sankararaman; Jialin Ding 001; Chuan Lei; Xiao Qin; Balakrishnan Narayanaswamy; Tim Kraska (CoRR, 2025)

TailorSQL: An NL2SQL System Tailored to Your Query Workload. - Kapil Vaidya; Jialin Ding 001; Sebastian Kosak; David Kernert; Chuan Lei; Xiao Qin; Abhinav Tripathy; Ramesh Balan; Balakrishnan Narayanaswamy; Tim Kraska (CoRR, 2025)

SQLens: An End-to-End Framework for Error Detection and Correction in Text-to-SQL. - Yue Gong; Chuan Lei; Xiao Qin; Kapil Vaidya; Balakrishnan Narayanaswamy; Tim Kraska (CoRR, 2025)