WCET estimation for executables in the presence of data caches. - Rathijit Sen; Y. N. Srikant (EMSOFT, 2007)

Executable Analysis using Abstract Interpretation with Circular Linear Progressions. - Rathijit Sen; Y. N. Srikant (MEMOCODE, 2007)

Cooperative crug isolation. - Aditya V. Thakur; Rathijit Sen; Ben Liblit; Shan Lu 001 (WODA, 2009)

Sound and Efficient WCET Analysis in the Presence of Timing Anomalies. - Jan Reineke 001; Rathijit Sen (WCET, 2009)

The gem5 simulator. - Nathan L. Binkert; Bradford M. Beckmann; Gabriel Black; Steven K. Reinhardt; Ali G. Saidi; Arkaprava Basu; Joel Hestness; Derek Hower; Tushar Krishna; Somayeh Sardashti; Rathijit Sen; Korey Sewell; et al. (SIGARCH Comput. Archit. News, 2011)

Reuse-based online models for caches. - Rathijit Sen; David A. Wood 001 (SIGMETRICS, 2013)

GPGPU Footprint Models to Estimate per-Core Power. - Rathijit Sen; David A. Wood 001 (IEEE Comput. Archit. Lett., 2016)

Frequency governors for cloud database OLTP workloads. - Rathijit Sen; Alan Halverson (ISLPED, 2017)

Energy-Proportional Computing: A New Definition. - Rathijit Sen; David A. Wood 001 (Computer, 2017)

ROSA: R Optimizations with Static Analysis. - Rathijit Sen; Jianqiao Zhu; Jignesh M. Patel; Somesh Jha (CoRR, 2017)

Pareto Governors for Energy-Optimal Computing. - Rathijit Sen; David A. Wood 001 (ACM Trans. Archit. Code Optim., 2017)

Characterizing Resource Sensitivity of Database Workloads. - Rathijit Sen; Karthik Ramachandra 002 (HPCA, 2018)

Peregrine: Workload Optimization for Cloud Query Engines. - Alekh Jindal; Hiren Patel; Abhishek Roy 008; Shi Qiao 001; Zhicheng Yin; Rathijit Sen; Subru Krishnan (SoCC, 2019)

Exploiting Intel Optane SSD for Microsoft SQL Server. - Kan Wu; Andrea C. Arpaci-Dusseau; Remzi H. Arpaci-Dusseau; Rathijit Sen; Kwanghyun Park 001 (DaMoN, 2019)

Performance Modeling and Bottleneck Analysis of EDGE Processors Using Dependence Graphs. - Hossein Golestani; Gagan Gupta 003; Rathijit Sen (IEEE Comput. Archit. Lett., 2019)

Cloudy with high chance of DBMS: a 10-year prediction for Enterprise-Grade ML. - Ashvin Agrawal; Rony Chatterjee; Carlo Curino; Avrilia Floratou; Neha Godwal; Matteo Interlandi; Alekh Jindal; Konstantinos Karanasos; Subru Krishnan; Brian Kroth; Jyoti Leeka; Kwanghyun Park 001; et al. (CIDR, 2020)

Extending Relational Query Processing with ML Inference. - Konstantinos Karanasos; Matteo Interlandi; Fotis Psallidas; Rathijit Sen; Kwanghyun Park 001; Ivan Popivanov; Doris Xin; Supun Nakandala; Subru Krishnan; Markus Weimer; Yuan Yu; Raghu Ramakrishnan 001; et al. (CIDR, 2020)

Lessons learned from the early performance evaluation of Intel optane DC persistent memory in DBMS. - Yinjun Wu; Kwanghyun Park 001; Rathijit Sen; Brian Kroth; Jaeyoung Do (DaMoN, 2020)

Automated tuning of query degree of parallelism via machine learning. - Zhiwei Fan; Rathijit Sen; Paraschos Koutris; Aws Albarghouthi (aiDM@SIGMOD, 2020)

A Comparative Exploration of ML Techniques for Tuning Query Degree of Parallelism. - Zhiwei Fan; Rathijit Sen; Paraschos Koutris; Aws Albarghouthi (CoRR, 2020)

AutoToken: Predicting Peak Parallelism for Big Data Analytics at Microsoft. - Rathijit Sen; Alekh Jindal; Hiren Patel; Shi Qiao 001 (Proc. VLDB Endow., 2020)

The Storage Hierarchy is Not a Hierarchy: Optimizing Caching on Modern Storage Devices with Orthus. - Kan Wu; Zhihan Guo; Guanzhou Hu; Kaiwei Tu; Ramnatthan Alagappan; Rathijit Sen; Kwanghyun Park 001; Andrea C. Arpaci-Dusseau; Remzi H. Arpaci-Dusseau (FAST, 2021)

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)

Microlearner: A fine-grained Learning Optimizer for Big Data Workloads at Microsoft. - Alekh Jindal; Shi Qiao 001; Rathijit Sen; Hiren Patel (ICDE, 2021)

Hardware Acceleration for DBMS Machine Learning Scoring: Is It Worth the Overheads? - Zahra Azad; Rathijit Sen; Kwanghyun Park 001; Ajay Joshi (ISPASS, 2021)

Performance Characterization of .NET Benchmarks. - Aniket Deshmukh 002; Ruihao Li 002; Rathijit Sen; Robert R. Henry; Monica Beckwith; Gagan Gupta 003 (ISPASS, 2021)

Optimal Resource Allocation for Serverless Queries. - Anish Pimpley; Shuo Li; Anubha Srivastava; Vishal Rohra; Yi Zhu; Soundararajan Srinivasan; Alekh Jindal; Hiren Patel; Shi Qiao 001; Rathijit Sen (CoRR, 2021)

AutoExecutor: Predictive Parallelism for Spark SQL Queries. - Rathijit Sen; Abhishek Roy 008; Alekh Jindal; Rui Fang; Jeff Zheng; Xiaolei Liu; Ruiping Li (Proc. VLDB Endow., 2021)

Towards Optimal Resource Allocation for Big Data Analytics. - Anish Pimpley; Shuo Li; Rathijit Sen; Soundararajan Srinivasan; Alekh Jindal (EDBT, 2022)

NyxCache: Flexible and Efficient Multi-tenant Persistent Memory Caching. - Kan Wu; Kaiwei Tu; Yuvraj Patel; Rathijit Sen; Kwanghyun Park 001; Andrea C. Arpaci-Dusseau; Remzi H. Arpaci-Dusseau (FAST, 2022)

Calipers: a criticality-aware framework for modeling processor performance. - Hossein Golestani; Rathijit Sen; Vinson Young; Gagan Gupta 003 (ICS, 2022)

End-to-end Optimization of Machine Learning Prediction Queries. - Kwanghyun Park 001; Karla Saur; Dalitso Banda; Rathijit Sen; Matteo Interlandi; Konstantinos Karanasos (SIGMOD Conference, 2022)

Share the Tensor Tea: How Databases can Leverage the Machine Learning Ecosystem. - Yuki Asada; Victor Fu; Apurva Gandhi; Advitya Gemawat; Lihao Zhang; Dong He 002; Vivek Gupta; Ehi Nosakhare; Dalitso Banda; Rathijit Sen; Matteo Interlandi (CoRR, 2022)

Share the Tensor Tea: How Databases can Leverage the Machine Learning Ecosystem. - Yuki Asada; Victor Fu; Apurva Gandhi; Advitya Gemawat; Lihao Zhang; Vivek Gupta; Ehi Nosakhare; Dalitso Banda; Rathijit Sen; Matteo Interlandi (Proc. VLDB Endow., 2022)

Query Processing on Tensor Computation Runtimes. - Dong He 002; Supun Chathuranga Nakandala; Dalitso Banda; Rathijit Sen; Karla Saur; Kwanghyun Park 001; Carlo Curino; Jesús Camacho-Rodríguez; Konstantinos Karanasos; Matteo Interlandi (Proc. VLDB Endow., 2022)

The Tensor Data Platform: Towards an AI-centric Database System. - Apurva Gandhi; Yuki Asada; Victor Fu; Advitya Gemawat; Lihao Zhang; Rathijit Sen; Carlo Curino; Jesús Camacho-Rodríguez; Matteo Interlandi (CIDR, 2023)

Query Processing on Gaming Consoles. - Wei Cui; Qianxi Zhang; Spyros Blanas; Jesús Camacho-Rodríguez; Brandon Haynes; Yinan Li; Ravi Ramamurthy; Peng Cheng 005; Rathijit Sen; Matteo Interlandi (DaMoN, 2023)

Random Forests over normalized data in CPU-GPU DBMSes. - Zezhou Huang; Pavan Kalyan Damalapati; Rathijit Sen; Eugene Wu 002 (DaMoN, 2023)

Microarchitectural Analysis of Graph BI Queries on RDBMS. - Rathijit Sen; Yuanyuan Tian 001 (DaMoN, 2023)

Predictive Price-Performance Optimization for Serverless Query Processing. - Rathijit Sen; Abhishek Roy 008; Alekh Jindal (EDBT, 2023)

Towards Building Autonomous Data Services on Azure. - Yiwen Zhu; Yuanyuan Tian 001; Joyce Cahoon; Subru Krishnan; Ankita Agarwal; Rana Alotaibi; Jesús Camacho-Rodríguez; Bibin Chundatt; Andrew Chung; Niharika Dutta; Andrew Fogarty; Anja Gruenheid; et al. (SIGMOD Conference Companion, 2023)

Revisiting Query Performance in GPU Database Systems. - Jiashen Cao; Rathijit Sen; Matteo Interlandi; Joy Arulraj; Hyesoon Kim (CoRR, 2023)

Runtime Variation in Big Data Analytics. - Yiwen Zhu; Rathijit Sen; Robert Horton; John Mark Agosta (Proc. ACM Manag. Data, 2023)

JoinBoost: Grow Trees Over Normalized Data Using Only SQL. - Zezhou Huang; Rathijit Sen; Jiaxiang Liu; Eugene Wu 002 (Proc. VLDB Endow., 2023)

Optimizing Data Pipelines for Machine Learning in Feature Stores. - Rui Liu; Kwanghyun Park 001; Fotis Psallidas; Xiaoyong Zhu; Jinghui Mo; Rathijit Sen; Matteo Interlandi; Konstantinos Karanasos; Yuanyuan Tian 001; Jesús Camacho-Rodríguez (Proc. VLDB Endow., 2023)

GPU Database Systems Characterization and Optimization. - Jiashen Cao; Rathijit Sen; Matteo Interlandi; Joy Arulraj; Hyesoon Kim (Proc. VLDB Endow., 2023)

Performance or Efficiency? A Tale of Two Cores for DB Workloads. - Rathijit Sen (DaMoN, 2024)

Rockhopper: A Robust Optimizer for Spark Configuration Tuning in Production Environment. - Yiwen Zhu; Rathijit Sen; Brian Kroth; Sergiy Matusevych; Andreas C. Mueller; Tengfei Huang; Rahul Challapalli; Weihan Tang; Xin He; Mo Liu 003; Estera Kot; Sule Kahraman; et al. (SIGMOD Conference Companion, 2025)

Terabyte-Scale Analytics in the Blink of an Eye. - Bowen Wu; Wei Cui; Carlo Curino; Matteo Interlandi; Rathijit Sen (CoRR, 2025)

GPU Acceleration of SQL Analytics on Compressed Data. - Zezhou Huang; Krystian Sakowski; Hans Lehnert; Wei Cui; Carlo Curino; Matteo Interlandi; Marius Dumitru; Rathijit Sen (CoRR, 2025)

Zorse: Optimizing LLM Training Efficiency on Heterogeneous GPU Clusters. - Runsheng Benson Guo; Utkarsh Anand; Khuzaima Daudjee; Rathijit Sen (CoRR, 2025)