RAUL CASTRO FERNANDEZ

Assistant Professor, Computer Science, The University of Chicago

Chicago, IL, USA

Office 245, John Crerar Library

raulcf at uchicago.edu

I am interested in the economics and value of data. The goal of my research is to understand how to make the best use of data possible. For that, I often build systems to share, discover, prepare, integrate, and process data. I often use techniques from data management, statistics, and machine learning. I'm part of ChiData, the data systems research group at The University of Chicago.

I'm always looking for great students and collaborators. If you are interested in doing a PhD or Postdoc with me, send me an email explaining your interest, and attach an up-to-date CV. If you are currently an undergraduate at UChicago and are interested in participating in a research project, send me an up-to-date CV and let's chat.

PUBLICATIONS

Preprint/Work in Progress

• 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 Work in progress

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 Elmore, Ian Foster, Michael Franklin, Sanjay Krishnan, Raul Castro Fernandez.VLDB 2022 (New)
• Revisiting Online Data Markets in 2022. A Seller and Buyer Perspective

  Javen Kennedy, Pranav Subramaniam, Sainyam Galhotra, Raul Castro Fernandez.SIGMOD Record (New)
• Enabling AI Innovation via Data and Model Sharing: An Overview of the Nsf Convergence Accelerator Track D

  Several authorsAI Magazine
• Protecting Data Markets from Strategic Buyers

  Raul Castro Fernandez.SIGMOD 2022
• Leva: Boosting Machine Learning Performance with Relational Embedding Data Augmentation Alex Zhao, Raul Castro Fernandez.SIGMOD 2022

2020

• Data Market Platforms: Trading Data Assets to Solve Data Problems Raul Castro Fernandez, Pranav Subramaniam, Michael Franklin.VLDB 2020
• ARDA: Automatic Relational Data Augmentation for Machine Learning Nadiia Chepurko, Ryan Marcus, Emanuel Zgraggen, Raul Castro Fernandez, Tim Kraska, David Karger. VLDB 2020
• Starling: A Scalable Query Engine on Cloud Function Services Matt Perron, Raul Castro Fernandez, David DeWitt, Samuel Madden. SIGMOD 2020
• A System for Studying Deep Network Training Raul Castro Fernandez CIDR'20 (Abstract)

2019

• Lazo A Cardinality-Based Method for Coupled Estimation of Jaccard Similarity and Containment. Raul Castro Fernandez, Jisoo Min, Demitri Devada, Samuel Madden. ICDE'19
• Termite: A System for Tunneling Through Heterogeneous Data. Raul Castro Fernandez, Samuel Madden. AIDM@SIGMOD'19
• Raha: A Configuration-Free Error Detection System. Mohammad Mahdavi, Ziawasch Abedjan, Raul Castro Fernandez, Sam Madden, Mourad Ouzzani, Michael Stonebraker, Nan Tang SIGMOD'19
• Aurum: A Story About Research Taste Raul Castro Fernandez. Making Databases Work. ACM Morgan & Claypool. 2019

2018

• Aurum: A Data Discovery System Raul Castro Fernandez, Ziawasch Abedjan, Famien Koko, Gina Yuan, Samuel Madden, Michael Stonebraker. ICDE'18
• Seeping Semantics: Linking Datasets using Word Embeddings for Data Discovery Raul Castro Fernandez, Essam Mansour, Abdulhakim Qahtan, Ahmed Elmagarmid, Ihab Ilyas, Samuel Madden, Mourad Ouzzani, Michael Stonebraker, Nan Tang. ICDE'18
• Meta-Dataflows: Efficient Exploratory Dataflow Jobs Raul Castro Fernandez, William Culhane, William Culhane, Pijika Watcharapichat, Matthias Weidlich, Victoria Lopez Morales, Peter Pietzuch. SIGMOD'18
• Extracting Syntactical Patterns from Databases Andrew Ilyas, Joana M. F. da Trindade, Raul Castro Fernandez, Samuel Madden. ICDE'18
• FAHES: A Robust Disguised Missing Values Detector Mourad Ouzzani, Nan Tang, Ahmed Elmagarmid, Raul Castro Fernandez, Abdulhakim A. Qahtan. KDD'18
• Building Data Civilizer Pipelines with an Advanced Workflow Engine Essam Mansour, Dong Deng, Raul Castro Fernandez, Abdulhakim Qahtan, Wenbo Tao, Ziawasch Abedjan, Ahmed Elmagarmid, Ihab Ilyas, Samuel Madden, Mourad Ouzzani, Michael Stonebraker, Nan Tang. (Demo) ICDE'18

2017

• Quill: Efficient, Transferable, and Rich Analytics at Scale Badrish Chandramouli, Raul Castro Fernandez, Jonathan Goldstein, Ahmed Eldawy, Abdul Quamar. VLDB'17
• The Data Civilizer System Dong Deng, Raul Castro Fernandez, Ziawasch Abedjan, Sibo Wang, Michael Stonebraker, Ahmed Elmagarmid, Ihab Ilyas, Samuel Madden, Mourad Ouzzani, Nan Tang. CIDR'17
• A Demo of the Data Civilizer System Raul Castro Fernandez, Dong Deng, Essam Mansour, Abdulhakim A Qahtan, Wenbo Tao, Ziawasch Abedjan, Ahmed Elmagarmid, Ihab Ilyas, Samuel Madden, Mourad Ouzzani, Michael Stonebraker, Nan Tang. (Demo) SIGMOD'17

2016

• Ako: Decentralised Deep Learning with Partial Gradient Exchange Pijika Watcharapichat, Victoria Lopez Morales, Raul Castro Fernandez, Peter Pietzuch. SOCC'16
• 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. VLDB'16
• Towards Large-Scale Data Discovery Raul Castro Fernandez, Ziawasch Abedjan, Samuel Madden, Michael Stonebraker. ExploreDB@SIGMOD'16
• SABER: Window-Based Hybrid Stream Processing for Heterogeneous Architectures Alexandros Koliousis, Matthias Weidlich, Raul Castro Fernandez, Paolo Costa, Alexander Wolf, Peter Pietzuch. SIGMOD'16
• Java2SDG: Stateful Big Data Processing for the Masses Raul Castro Fernandez, Panagiotis Garefalakis, Peter Pietzuch. (Demo) ICDE'16

2015

• Liquid: Unifying Nearline and Offline Big Data Integration Raul Castro Fernandez, Peter Pietzuch, Joel Koshy, Jay Kreps, Dong Lin, Neha Narkhede, Jun Rao, Chris Riccomini, Guozhang Wang. CIDR'15

2014

• Making State Explicit for Imperative Big Data Processing Raul Castro Fernandez, Matteo Migliavacca, Evangelia Kalyvianaki and Peter Pietzuch. USENIX ATC'14
• Grand Challenge Scalable Stateful Stream Processing for Smart Grids Raul Castro Fernandez, Matthias Weidlich, Peter Pietzuch and Avigdor Gal. DEBS'14

2013

• Integrating Scale Out and Fault Tolerance in Stream Processing using Operator State Management Raul Castro Fernandez, Matteo Migliavacca, Evangelia Kalyvianaki and Peter Pietzuch. SIGMOD'13
• Towards Low-Latency and In-Memory Large-Scale Data Processing Raul Castro Fernandez and Peter Pietzuch. PhD Workshop@DEBS'13

STUDENTS

Below I include Postdocs, PhD, and Master students. In addition to these, I'm fortunate to work with great undergraduate students and occasionally with external students.

Postdocs and PhD Students

• Sainyam Galhotra
• Qiming Wang
• Pranav Subramaniam
• Yue Gong
• Zhiru Zhu
• Tapan Srivastava
• Steven Xia

Master and Undergraduate Students

• Zach Hempstead
• Stanley Zhu
• Abida Aisikaer
• Chris Zhu

Alumni

• Alex Zhao
• Jenny Long
• Yintong Ma
• Ipsita Mohanty

TEACHING, SERVICE, BIO

Teaching

• The Value of Data (Fall'20, Fall'21)
• Ethics, Fairness, Responsibility, and Privacy in Data Science (Spring'20, Spring'21)

• Introduction to Databases (Winter'20, Winter'21)

Service

• SIGMOD'24 PC Member

• SIGMOD'23 PC Member

• VLDB'23 PC Member and publicity chair

• HPTS'22 PC Member

• SIGMOD'22 PC Member and publicity chair

• VLDB'22 PC Member and Workshop Co-Chair

• KDD'21 PC Member

• SIGMOD'21 PC Member (Demo track)

• VLDB'21 PC Member (Distinguished Reviewer Award)

• ICDE'21 PC Member

• VLDB'20 PC Member

• SoCC'20 PC Member

• SIGMOD'19 PC Member (Distinguished Reviewer Award)

• VLDBJ Reviewer

• TKDE Reviewer

• TODS Reviewer

Bio

I completed a postdoc at MIT working with Sam Madden. Before that, I obtained my PhD at Imperial College London working with Peter Pietzuch.