Reservation-based Scheduling: If You're Late Don't Blame Us! - Carlo Curino; Djellel Eddine Difallah; Chris Douglas; Subru Krishnan; Raghu Ramakrishnan 001; Sriram Rao (SoCC, 2014)

PerfOrator: eloquent performance models for Resource Optimization. - Kaushik Rajan; Dharmesh Kakadia; Carlo Curino; Subru Krishnan (SoCC, 2016)

Morpheus: Towards Automated SLOs for Enterprise Clusters. - Sangeetha Abdu Jyothi; Carlo Curino; Ishai Menache; Shravan Matthur Narayanamurthy; Alexey Tumanov; Jonathan Yaniv; Ruslan Mavlyutov; Iñigo Goiri; Subru Krishnan; Janardhan Kulkarni; Sriram Rao (OSDI, 2016)

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)

Griffon: Reasoning about Job Anomalies with Unlabeled Data in Cloud-based Platforms. - Liqun Shao; Yiwen Zhu; Siqi Liu; Abhiram Eswaran; Kristin Lieber; Janhavi Suresh Mahajan; Minsoo Thigpen; Sudhir Darbha; Subru Krishnan; Soundar Srinivasan; Carlo Curino; Konstantinos Karanasos (SoCC, 2019)

Hydra: a federated resource manager for data-center scale analytics. - Carlo Curino; Subru Krishnan; Konstantinos Karanasos; Sriram Rao; Giovanni Matteo Fumarola; Botong Huang; Kishore Chaliparambil; Arun Suresh; Young Chen; Solom Heddaya; Roni Burd; Sarvesh Sakalanaga; et al. (NSDI, 2019)

Peering through the Dark: An Owl's View of Inter-job Dependencies and Jobs' Impact in Shared Clusters. - Andrew Chung; Carlo Curino; Subru Krishnan; Konstantinos Karanasos; Panagiotis Garefalakis; Gregory R. Ganger (SIGMOD Conference, 2019)

Data Science through the looking glass and what we found there. - Fotis Psallidas; Yiwen Zhu; Bojan Karlas; Matteo Interlandi; Avrilia Floratou; Konstantinos Karanasos; Wentao Wu 001; Ce Zhang 001; Subru Krishnan; Carlo Curino; Markus Weimer (CoRR, 2019)

SparkCruise: Handsfree Computation Reuse in Spark. - Abhishek Roy 008; Alekh Jindal; Hiren Patel; Ashit Gosalia; Subru Krishnan; Carlo Curino (Proc. VLDB Endow., 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)

Vamsa: Automated Provenance Tracking in Data Science Scripts. - Mohammad Hossein Namaki; Avrilia Floratou; Fotis Psallidas; Subru Krishnan; Ashvin Agrawal; Yinghui Wu; Yiwen Zhu; Markus Weimer (KDD, 2020)

Unearthing inter-job dependencies for better cluster scheduling. - Andrew Chung; Subru Krishnan; Konstantinos Karanasos; Carlo Curino; Gregory R. Ganger (OSDI, 2020)

Vamsa: Tracking Provenance in Data Science Scripts. - Mohammad Hossein Namaki; Avrilia Floratou; Fotis Psallidas; Subru Krishnan; Ashvin Agrawal; Yinghui Wu (CoRR, 2020)

KEA: Tuning an Exabyte-Scale Data Infrastructure. - Yiwen Zhu; Subru Krishnan; Konstantinos Karanasos; Isha Tarte; Conor Power; Abhishek Modi; Manoj Kumar; Deli Zhang; Kartheek Muthyala; Nick Jurgens; Sarvesh Sakalanaga; Sudhir Darbha; et al. (SIGMOD Conference, 2021)

Doppler: Automated SKU Recommendation in Migrating SQL Workloads to the Cloud. - Joyce Cahoon; Wenjing Wang 005; Yiwen Zhu; Katherine Lin; Sean Liu; Raymond Truong; Neetu Singh; Chengcheng Wan 001; Alexandra M. Ciortea; Sreraman Narasimhan; Subru Krishnan (Proc. VLDB Endow., 2022)

Data Science Through the Looking Glass: Analysis of Millions of GitHub Notebooks and ML.NET Pipelines. - Fotis Psallidas; Yiwen Zhu; Bojan Karlas; Jordan Henkel; Matteo Interlandi; Subru Krishnan; Brian Kroth; K. Venkatesh Emani; Wentao Wu 001; Ce Zhang 001; Markus Weimer; Avrilia Floratou; et al. (SIGMOD Rec., 2022)

Stitcher: Learned Workload Synthesis from Historical Performance Footprints. - Chengcheng Wan 001; Yiwen Zhu; Joyce Cahoon; Wenjing Wang 005; Katherine Lin; Sean Liu; Raymond Truong; Neetu Singh; Alexandra M. Ciortea; Konstantinos Karanasos; Subru Krishnan (EDBT, 2023)

Schema Matching using Pre-Trained Language Models. - Yunjia Zhang; Avrilia Floratou; Joyce Cahoon; Subru Krishnan; Andreas C. Müller 002; Dalitso Banda; Fotis Psallidas; Jignesh M. Patel (ICDE, 2023)

Demonstration of Geyser: Provenance Extraction and Applications over Data Science Scripts. - Fotis Psallidas; Megan Eileen Leszczynski; Mohammad Hossein Namaki; Avrilia Floratou; Ashvin Agrawal; Konstantinos Karanasos; Subru Krishnan; Pavle Subotic; Markus Weimer; Yinghui Wu; Yiwen Zhu (SIGMOD Conference Companion, 2023)

Towards Building Autonomous Data Services on Azure. - Yiwen Zhu; Yuanyuan Tian; 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)

Lorentz: Learned SKU Recommendation Using Profile Data. - Nick Glaze; Tria McNeely; Yiwen Zhu; Matthew Gleeson; Helen Serr; Rajeev Bhopi; Subru Krishnan (Proc. ACM Manag. Data, 2024)

Intelligent Pooling: Proactive Resource Provisioning in Large-scale Cloud Service. - Deepak Ravikumar; Alex Yeo; Yiwen Zhu; Aditya Lakra; Harsha Nagulapalli; Santhosh Ravindran; Steve Suh; Niharika Dutta; Andrew Fogarty; Yoonjae Park; Sumeet Khushalani; Arijit Tarafdar; et al. (Proc. VLDB Endow., 2024)