The Case for Unifying Data Loading in Machine Learning Clusters. - Aarati Kakaraparthy; Abhay Venkatesh; Amar Phanishayee; Shivaram Venkataraman (HotCloud, 2019)

Optimizing Databases by Learning Hidden Parameters of Solid State Drives. - Aarati Kakaraparthy; Jignesh M. Patel; Kwanghyun Park 001; Brian Kroth (Proc. VLDB Endow., 2019)

FPGA for Aggregate Processing: The Good, The Bad, and The Ugly. - Zubeyr F. Eryilmaz; Aarati Kakaraparthy; Jignesh M. Patel; Rathijit Sen; Kwanghyun Park 001 (ICDE, 2021)

VIP Hashing - Adapting to Skew in Popularity of Data on the Fly (extended version). - Aarati Kakaraparthy; Jignesh M. Patel; Brian P. Kroth; Kwanghyun Park 001 (CoRR, 2022)

VIP Hashing - Adapting to Skew in Popularity of Data on the Fly. - Aarati Kakaraparthy; Jignesh M. Patel; Brian Kroth; Kwanghyun Park 001 (Proc. VLDB Endow., 2022)

Tenant Placement in Over-subscribed Database-as-a-Service Clusters. - Arnd Christian König; Yi Shan; Tobias Ziegler 001; Aarati Kakaraparthy; Willis Lang; Justin Moeller; Ajay Kalhan; Vivek R. Narasayya (Proc. VLDB Endow., 2022)

SplitDF: Splitting Dataframes for Memory-Efficient Data Analysis. - Aarati Kakaraparthy; Jignesh M. Patel (Proc. VLDB Endow., 2024)

Fine-Grained Hardware Profiling - Are You Using the Right Tools? - Aarati Kakaraparthy; Jignesh M. Patel (SIGMOD Rec., 2024)