K-means++ vs. Behavioral Biometrics: One Loop to Rule Them All. - Parimarjan Negi; Prafull Sharma; Vivek Jain; Bahman Bahmani (NDSS, 2018)

Evaluating End-to-End Optimization for Data Analytics Applications in Weld. - Shoumik Palkar; James Thomas 003; Deepak Narayanan; Pratiksha Thaker; Rahul Palamuttam; Parimarjan Negi; Anil Shanbhag; Malte Schwarzkopf; Holger Pirk; Saman P. Amarasinghe; Samuel Madden 001; Matei Zaharia (Proc. VLDB Endow., 2018)

Park: An Open Platform for Learning-Augmented Computer Systems. - Hongzi Mao; Parimarjan Negi; Akshay Narayan 001; Hanrui Wang 002; Jiacheng Yang; Haonan Wang; Ryan Marcus; Ravichandra Addanki; Mehrdad Khani Shirkoohi; Songtao He; Vikram Nathan; Frank Cangialosi; et al. (NeurIPS, 2019)

Neo: A Learned Query Optimizer. - Ryan Marcus; Parimarjan Negi; Hongzi Mao; Chi Zhang 068; Mohammad Alizadeh; Tim Kraska; Olga Papaemmanouil; Nesime Tatbul (Proc. VLDB Endow., 2019)

Cost-Guided Cardinality Estimation: Focus Where it Matters. - Parimarjan Negi; Ryan Marcus; Hongzi Mao; Nesime Tatbul; Tim Kraska; Mohammad Alizadeh (ICDE Workshops, 2020)

High Throughput Cryptocurrency Routing in Payment Channel Networks. - Vibhaalakshmi Sivaraman; Shaileshh Bojja Venkatakrishnan; Kathleen Ruan; Parimarjan Negi; Lei Yang 031; Radhika Mittal; Giulia Fanti; Mohammad Alizadeh (NSDI, 2020)

Bao: Learning to Steer Query Optimizers. - Ryan Marcus; Parimarjan Negi; Hongzi Mao; Nesime Tatbul; Mohammad Alizadeh; Tim Kraska (CoRR, 2020)

Steering Query Optimizers: A Practical Take on Big Data Workloads. - Parimarjan Negi; Matteo Interlandi; Ryan Marcus; Mohammad Alizadeh; Tim Kraska; Marc T. Friedman; Alekh Jindal (SIGMOD Conference, 2021)

Flow-Loss: Learning Cardinality Estimates That Matter. - Parimarjan Negi; Ryan Marcus; Andreas Kipf; Hongzi Mao; Nesime Tatbul; Tim Kraska; Mohammad Alizadeh (Proc. VLDB Endow., 2021)

Bao: Making Learned Query Optimization Practical. - Ryan Marcus; Parimarjan Negi; Hongzi Mao; Nesime Tatbul; Mohammad Alizadeh; Tim Kraska (SIGMOD Rec., 2022)

Unshackling Database Benchmarking from Synthetic Workloads. - Parimarjan Negi; Laurent Bindschaedler; Mohammad Alizadeh; Tim Kraska; Jyoti Leeka; Anja Gruenheid; Matteo Interlandi (ICDE, 2023)

FactorJoin: A New Cardinality Estimation Framework for Join Queries. - Ziniu Wu; Parimarjan Negi; Mohammad Alizadeh; Tim Kraska; Samuel Madden 001 (Proc. ACM Manag. Data, 2023)

Robust Query Driven Cardinality Estimation under Changing Workloads. - Parimarjan Negi; Ziniu Wu; Andreas Kipf; Nesime Tatbul; Ryan Marcus; Sam Madden 001; Tim Kraska; Mohammad Alizadeh (Proc. VLDB Endow., 2023)

Stage: Query Execution Time Prediction in Amazon Redshift. - Ziniu Wu; Ryan Marcus; Zhengchun Liu; Parimarjan Negi; Vikram Nathan; Pascal Pfeil; Gaurav Saxena; Mohammad Rahman; Balakrishnan Narayanaswamy; Tim Kraska (SIGMOD Conference Companion, 2024)

Machine Learning for Out of Distribution Database Workloads - Parimarjan Negi (2024)