Self-Regulating Streaming Systems: Challenges and Opportunities. - Avrilia Floratou; Ashvin Agrawal (BIRTE, 2017)

Twitter Heron: Towards Extensible Streaming Engines. - Maosong Fu; Ashvin Agrawal; Avrilia Floratou; Bill Graham; Andrew Jorgensen; Mark Li; Neng Lu; Karthik Ramasamy; Sriram Rao; Cong Wang (ICDE, 2017)

Dhalion: Self-Regulating Stream Processing in Heron. - Avrilia Floratou; Ashvin Agrawal; Bill Graham; Sriram Rao; Karthik Ramasamy (Proc. VLDB Endow., 2017)

Netco: Cache and I/O Management for Analytics over Disaggregated Stores. - Virajith Jalaparti; Chris Douglas; Mainak Ghosh; Ashvin Agrawal; Avrilia Floratou; Srikanth Kandula; Ishai Menache; Joseph (Seffi) Naor; Sriram Rao (SoCC, 2018)

Dhalion in Action: Automatic Management of Streaming Applications. - Ashvin Agrawal; Avrilia Floratou (Proc. VLDB Endow., 2018)

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)

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)

Spur: Mitigating Slow Instances in Large-Scale Streaming Pipelines. - Ke Wang; Avrilia Floratou; Ashvin Agrawal; Daniel Musgrave (SIGMOD Conference, 2020)

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

OneProvenance: Efficient Extraction of Dynamic Coarse-Grained Provenance from Database Logs. - Fotis Psallidas; Ashvin Agrawal; Chandru Sugunan; Khaled Ibrahim; Konstantinos Karanasos; Jesús Camacho-Rodríguez; Avrilia Floratou; Carlo Curino; Raghu Ramakrishnan 001 (CoRR, 2022)

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)

OneProvenance: Efficient Extraction of Dynamic Coarse-Grained Provenance From Database Query Event Logs. - Fotis Psallidas; Ashvin Agrawal; Chandru Sugunan; Khaled Ibrahim; Konstantinos Karanasos; Jesús Camacho-Rodríguez; Avrilia Floratou; Carlo Curino; Raghu Ramakrishnan 001 (Proc. VLDB Endow., 2023)

XTable in Action: Seamless Interoperability in Data Lakes. - Ashvin Agrawal; Tim Brown; Anoop Johnson; Jesús Camacho-Rodríguez; Kyle Weller; Carlo Curino; Raghu Ramakrishnan 001 (CoRR, 2024)

Towards Query Optimizer as a Service (QOaaS) in a Unified LakeHouse Ecosystem: Can One QO Rule Them All? - Rana Alotaibi; Yuanyuan Tian 001; Stefan Grafberger; Jesús Camacho-Rodríguez; Nicolas Bruno; Brian Kroth; Sergiy Matusevych; Ashvin Agrawal; Mahesh Behera; Ashit Gosalia; César A. Galindo-Legaria; Milind Joshi; et al. (CoRR, 2024)

LST-Bench: Benchmarking Log-Structured Tables in the Cloud. - Jesús Camacho-Rodríguez; Ashvin Agrawal; Anja Gruenheid; Ashit Gosalia; Cristian Petculescu; Josep Aguilar-Saborit; Avrilia Floratou; Carlo Curino; Raghu Ramakrishnan 001 (Proc. ACM Manag. Data, 2024)