Raul Castro Fernandez

According to our database, Raul Castro Fernandez authored at least 65 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Saving Money for Analytical Workloads in the Cloud.

Tapan Srivastava, Raul Castro Fernandez

Proc. VLDB Endow., July, 2024

Nexus: Correlation Discovery over Collections of Spatio-Temporal Tabular Data.

Yue Gong, Sainyam Galhotra, Raul Castro Fernandez

Proc. ACM Manag. Data, 2024

FabricQA-Extractor: A Question Answering System to Extract Information from Documents using Natural Language Questions.

Qiming Wang, Raul Castro Fernandez

CoRR, 2024

Programmable Dataflows: Abstraction and Programming Model for Data Sharing.

Siyuan Xia, Chris Zhu, Tapan Srivastava, Bridget Fahey, Raul Castro Fernandez

CoRR, 2024

Controlling Dataflows with a Bolt-on Data Escrow.

Zhiru Zhu, Raul Castro Fernandez

CoRR, 2024

Demonstrating Nexus for Correlation Discovery over Collections of Spatio-Temporal Tabular Data.

Yue Gong, Raul Castro Fernandez

Proceedings of the Companion of the 2024 International Conference on Management of Data, 2024

Responsible Sharing of Spatiotemporal Data.

Raul Castro Fernandez, Arnab Nandi

Proceedings of the Companion of the 2024 International Conference on Management of Data, 2024

Demonstration of Ver: View Discovery in the Wild.

Kevin Dharmawan, Chirag A. Kawediya, Yue Gong, Zaki Indra Yudhistira, Zhiru Zhu, Sainyam Galhotra, Adila Alfa Krisnadhi, Raul Castro Fernandez

Proceedings of the Companion of the 2024 International Conference on Management of Data, 2024

2023

Solo: Data Discovery Using Natural Language Questions Via A Self-Supervised Approach.

Qiming Wang, Raul Castro Fernandez

Proc. ACM Manag. Data, December, 2023

Cackle: Analytical Workload Cost and Performance Stability With Elastic Pools.

Matthew Perron, Raul Castro Fernandez, David J. DeWitt, Michael J. Cafarella, Samuel Madden

Proc. ACM Manag. Data, December, 2023

Data and AI Model Markets: Opportunities for Data and Model Sharing, Discovery, and Integration.

Jian Pei, Raul Castro Fernandez, Xiaohui Yu

Proc. VLDB Endow., 2023

Saibot: A Differentially Private Data Search Platform.

Zezhou Huang, Jiaxiang Liu, Daniel Alabi, Raul Castro Fernandez, Eugene Wu

Proc. VLDB Endow., 2023

How Large Language Models Will Disrupt Data Management.

Raul Castro Fernandez, Aaron J. Elmore, Michael J. Franklin, Sanjay Krishnan, Chenhao Tan

Proc. VLDB Endow., 2023

Data-Sharing Markets: Model, Protocol, and Algorithms to Incentivize the Formation of Data-Sharing Consortia.

Raul Castro Fernandez

Proc. ACM Manag. Data, 2023

A Data-Centric Online Market for Machine Learning: From Discovery to Pricing.

Minbiao Han, Jonathan Light, Steven Xia, Sainyam Galhotra, Raul Castro Fernandez, Haifeng Xu

CoRR, 2023

Making Differential Privacy Easier to Use for Data Controllers and Data Analysts using a Privacy Risk Indicator and an Escrow-Based Platform.

Zhiru Zhu, Raul Castro Fernandez

CoRR, 2023

Kitana: Efficient Data Augmentation Search for AutoML.

Zezhou Huang, Pranav Subramaniam, Raul Castro Fernandez, Eugene Wu

CoRR, 2023

Data Discovery using Natural Language Questions via a Self-Supervised Approach.

Qiming Wang, Raul Castro Fernandez

CoRR, 2023

Addressing Budget Allocation and Revenue Allocation in Data Market Environments Using an Adaptive Sampling Algorithm.

Boxin Zhao, Boxiang Lyu, Raul Castro Fernandez, Mladen Kolar

Proceedings of the International Conference on Machine Learning, 2023

Ver: View Discovery in the Wild.

Yue Gong, Zhiru Zhu, Sainyam Galhotra, Raul Castro Fernandez

Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

Metam: Goal-Oriented Data Discovery.

Sainyam Galhotra, Yue Gong, Raul Castro Fernandez

Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

2022

Revisiting Online Data Markets in 2022: A Seller and Buyer Perspective.

Javen Kennedy, Pranav Subramaniam, Sainyam Galhotra, Raul Castro Fernandez

SIGMOD Rec., 2022

Data Station: Delegated, Trustworthy, and Auditable Computation to Enable Data-Sharing Consortia with a Data Escrow.

Siyuan Xia, Zhiru Zhu, Chris Zhu, Jinjin Zhao, Kyle Chard, Aaron J. Elmore, Ian T. Foster, Michael J. Franklin, Sanjay Krishnan, Raul Castro Fernandez

Proc. VLDB Endow., 2022

Enabling AI Innovation via Data and Model Sharing: An Overview of the Nsf Convergence Accelerator Track D.

Chaitanya K. Baru, Michael Pozmantier, Ilkay Altintas, Stephen Baek, Jonathan Cohen, Laura E. Condon, Giulia Fanti, Raul Castro Fernandez, Ethan Jackson, Upmanu Lall, Bennett A. Landman, Hai Li, Claudia Marin, Beatriz Martínez-López, Dimitris N. Metaxas, Bradley D. Olsen, Grier P. Page, Yelda Turkan, Jingbo Zhang, Peng Zhang

AI Mag., 2022

Leva: Boosting Machine Learning Performance with Relational Embedding Data Augmentation.

Zixuan Zhao, Raul Castro Fernandez

Proceedings of the SIGMOD '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12, 2022

Protecting Data Markets from Strategic Buyers.

Raul Castro Fernandez

Proceedings of the SIGMOD '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12, 2022

2021

Niffler: A Reference Architecture and System Implementation for View Discovery over Pathless Table Collections by Example.

Yue Gong, Zhiru Zhu, Sainyam Galhotra, Raul Castro Fernandez

CoRR, 2021

Comprehensive and Comprehensible Data Catalogs: The What, Who, Where, When, Why, and How of Metadata Management.

Pranav Subramaniam, Yintong Ma, Chi Li, Ipsita Mohanty, Raul Castro Fernandez

CoRR, 2021

2020

Data Market Platforms: Trading Data Assets to Solve Data Problems.

Raul Castro Fernandez, Pranav Subramaniam, Michael J. Franklin

Proc. VLDB Endow., 2020

ARDA: Automatic Relational Data Augmentation for Machine Learning.

Nadiia Chepurko, Ryan Marcus, Emanuel Zgraggen, Raul Castro Fernandez, Tim Kraska, David R. Karger

Proc. VLDB Endow., 2020

The Data Station: Combining Data, Compute, and Market Forces.

Raul Castro Fernandez, Kyle Chard, Ben Blaiszik, Sanjay Krishnan, Aaron J. Elmore, Ziad Obermeyer, Josh Risley, Sendhil Mullainathan, Michael J. Franklin, Ian T. Foster

CoRR, 2020

Data Market Platforms: Trading Data Assets to Solve Data Problems [Vision Paper].

Raul Castro Fernandez, Pranav Subramaniam, Michael J. Franklin

CoRR, 2020

Starling: A Scalable Query Engine on Cloud Functions.

Matthew Perron, Raul Castro Fernandez, David J. DeWitt, Samuel Madden

Proceedings of the 2020 International Conference on Management of Data, 2020

A System for Studying Deep Network Training.

Raul Castro Fernandez

Proceedings of the 10th Conference on Innovative Data Systems Research, 2020

2019

Dataset-On-Demand: Automatic View Search and Presentation for Data Discovery.

Raul Castro Fernandez, Nan Tang, Mourad Ouzzani, Michael Stonebraker, Samuel Madden

CoRR, 2019

Starling: A Scalable Query Engine on Cloud Function Services.

Matthew Perron, Raul Castro Fernandez, David J. DeWitt, Samuel Madden

CoRR, 2019

Raha: A Configuration-Free Error Detection System.

Mohammad Mahdavi, Ziawasch Abedjan, Raul Castro Fernandez, Samuel Madden, Mourad Ouzzani, Michael Stonebraker, Nan Tang

Proceedings of the 2019 International Conference on Management of Data, 2019

Termite: a system for tunneling through heterogeneous data.

Raul Castro Fernandez, Samuel Madden

Proceedings of the Second International Workshop on Exploiting Artificial Intelligence Techniques for Data Management, 2019

Lazo: A Cardinality-Based Method for Coupled Estimation of Jaccard Similarity and Containment.

Raul Castro Fernandez, Jisoo Min, Demitri Nava, Samuel Madden

Proceedings of the 35th IEEE International Conference on Data Engineering, 2019

Data civilizer: end-to-end support for data discovery, integration, and cleaning.

Mourad Ouzzani, Nan Tang, Raul Castro Fernandez

Proceedings of the Making Databases Work: the Pragmatic Wisdom of Michael Stonebraker, 2019

Aurum: a story about research taste.

Raul Castro Fernandez

Proceedings of the Making Databases Work: the Pragmatic Wisdom of Michael Stonebraker, 2019

2018

Smallify: Learning Network Size while Training.

Guillaume Leclerc, Manasi Vartak, Raul Castro Fernandez, Tim Kraska, Samuel Madden

CoRR, 2018

Meta-Dataflows: Efficient Exploratory Dataflow Jobs.

Raul Castro Fernandez, William Culhane, Pijika Watcharapichat, Matthias Weidlich, Victoria Lopez Morales, Peter R. Pietzuch

Proceedings of the 2018 International Conference on Management of Data, 2018

FAHES: A Robust Disguised Missing Values Detector.

Abdulhakim Ali Qahtan, Ahmed K. Elmagarmid, Raul Castro Fernandez, Mourad Ouzzani, Nan Tang

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Building Data Civilizer Pipelines with an Advanced Workflow Engine.

Essam Mansour, Dong Deng, Raul Castro Fernandez, Abdulhakim Ali Qahtan, Wenbo Tao, Ziawasch Abedjan, Ahmed K. Elmagarmid, Ihab F. Ilyas, Samuel Madden, Mourad Ouzzani, Michael Stonebraker, Nan Tang

Proceedings of the 34th IEEE International Conference on Data Engineering, 2018

Extracting Syntactical Patterns from Databases.

Andrew Ilyas, Joana M. F. da Trindade, Raul Castro Fernandez, Samuel Madden

Proceedings of the 34th IEEE International Conference on Data Engineering, 2018

Seeping Semantics: Linking Datasets Using Word Embeddings for Data Discovery.

Raul Castro Fernandez, Essam Mansour, Abdulhakim Ali Qahtan, Ahmed K. Elmagarmid, Ihab F. Ilyas, Samuel Madden, Mourad Ouzzani, Michael Stonebraker, Nan Tang

Proceedings of the 34th IEEE International Conference on Data Engineering, 2018

Aurum: A Data Discovery System.

Raul Castro Fernandez, Ziawasch Abedjan, Famien Koko, Gina Yuan, Samuel Madden, Michael Stonebraker

Proceedings of the 34th IEEE International Conference on Data Engineering, 2018

2017

Extracting Syntactic Patterns from Databases.

Andrew Ilyas, Joana M. F. da Trindade, Raul Castro Fernandez, Samuel Madden

CoRR, 2017

What to do about database decay.

Michael Stonebraker, Raul Castro Fernandez, Dong Deng, Michael L. Brodie

Commun. ACM, 2017

A Demo of the Data Civilizer System.

Raul Castro Fernandez, Dong Deng, Essam Mansour, Abdulhakim Ali Qahtan, Wenbo Tao, Ziawasch Abedjan, Ahmed K. Elmagarmid, Ihab F. Ilyas, Samuel Madden, Mourad Ouzzani, Michael Stonebraker, Nan Tang

Proceedings of the 2017 ACM International Conference on Management of Data, 2017

The Data Civilizer System.

Dong Deng, Raul Castro Fernandez, Ziawasch Abedjan, Sibo Wang, Michael Stonebraker, Ahmed K. Elmagarmid, Ihab F. Ilyas, Samuel Madden, Mourad Ouzzani, Nan Tang

Proceedings of the 8th Biennial Conference on Innovative Data Systems Research, 2017

2016

Stateful data-parallel processing.

Raul Castro Fernandez

PhD thesis, 2016

Quill: Efficient, Transferable, and Rich Analytics at Scale.

Badrish Chandramouli, Raul Castro Fernandez, Jonathan Goldstein, Ahmed Eldawy, Abdul Quamar

Proc. VLDB Endow., 2016

Detecting Data Errors: Where are we and what needs to be done?

Ziawasch Abedjan, Xu Chu, Dong Deng, Raul Castro Fernandez, Ihab F. Ilyas, Mourad Ouzzani, Paolo Papotti, Michael Stonebraker, Nan Tang

Proc. VLDB Endow., 2016

SABER: Window-Based Hybrid Stream Processing for Heterogeneous Architectures.

Alexandros Koliousis, Matthias Weidlich, Raul Castro Fernandez, Alexander L. Wolf, Paolo Costa, Peter R. Pietzuch

Proceedings of the 2016 International Conference on Management of Data, 2016

Towards large-scale data discovery: position paper.

Raul Castro Fernandez, Ziawasch Abedjan, Samuel Madden, Michael Stonebraker

Proceedings of the Third International Workshop on Exploratory Search in Databases and the Web, 2016

Java2SDG: Stateful big data processing for the masses.

Raul Castro Fernandez, Panagiotis Garefalakis, Peter R. Pietzuch

Proceedings of the 32nd IEEE International Conference on Data Engineering, 2016

The SABER system for window-based hybrid stream processing with GPGPUs: demo.

Alexandros Koliousis, Matthias Weidlich, Raul Castro Fernandez, Alexander L. Wolf, Paolo Costa, Peter R. Pietzuch

Proceedings of the 10th ACM International Conference on Distributed and Event-based Systems, 2016

Ako: Decentralised Deep Learning with Partial Gradient Exchange.

Pijika Watcharapichat, Victoria Lopez Morales, Raul Castro Fernandez, Peter R. Pietzuch

Proceedings of the Seventh ACM Symposium on Cloud Computing, 2016

2015

Liquid: Unifying Nearline and Offline Big Data Integration.

Raul Castro Fernandez, Peter R. Pietzuch, Jay Kreps, Neha Narkhede, Jun Rao, Joel Koshy, Dong Lin, Chris Riccomini, Guozhang Wang

Proceedings of the Seventh Biennial Conference on Innovative Data Systems Research, 2015

2014

Making State Explicit for Imperative Big Data Processing.

Raul Castro Fernandez, Matteo Migliavacca, Evangelia Kalyvianaki, Peter R. Pietzuch

Proceedings of the 2014 USENIX Annual Technical Conference, 2014

Scalable stateful stream processing for smart grids.

Raul Castro Fernandez, Matthias Weidlich, Peter R. Pietzuch, Avigdor Gal

Proceedings of the 8th ACM International Conference on Distributed Event-Based Systems, 2014

2013

Integrating scale out and fault tolerance in stream processing using operator state management.

Raul Castro Fernandez, Matteo Migliavacca, Evangelia Kalyvianaki, Peter R. Pietzuch

Proceedings of the ACM SIGMOD International Conference on Management of Data, 2013

Scalable and Fault-tolerant Stateful Stream Processing.

Raul Castro Fernandez, Matteo Migliavacca, Evangelia Kalyvianaki, Peter R. Pietzuch

Proceedings of the 2013 Imperial College Computing Student Workshop, 2013