Raul Castro Fernandez is an Assistant Professor of Computer Science at the University of Chicago, where he researches data ecology, a concept he created to study how data shapes our world and how we can shape it back. He is the faculty co-lead of the Data Science Institute's Data Ecology Research Initiative and a member of ChiData, the data systems research group at the University of Chicago. He is also co-founder and Chief Research Officer at invocate and co-runs Chicago Data Night, a forum connecting industry and academia in Chicago. Castro Fernandez's research focuses on data ecology, data discovery, data markets, and data integration. He develops both theory and systems that help people and organizations find, evaluate, and use data effectively. His work often uses techniques from data management, statistics, and machine learning. He has pioneered concepts in data market design, understanding the economics of data, and building platforms to support markets of data. His research on data ecology frames how data moves through and transforms technological, economic, and social systems—and how to design interventions to make those ecosystems more valuable, equitable, and resilient. His publications reveal a strong focus on data markets, data discovery, and LLM applications for data management. Recent work includes Pneuma (leveraging LLMs for tabular data), Solo (data discovery using natural language), and Nexus (correlation discovery for spatio-temporal data). His research spans theoretical foundations of data value to practical systems for data sharing and discovery. SIGMOD Test of Time Award (2023) NSF CAREER Award (2024) Sloan Research Fellowship (2025) Castro Fernandez has advised numerous PhD, Master's, and undergraduate students who have gone on to pursue PhDs at institutions like University of Washington and Stony Brook, joined companies like Google, Anthropic, and Citadel, or founded startups. His teaching includes courses on The Value of Data, Ethics in Data Science, and Introduction to Databases. He serves on program committees for major conferences including SIGMOD, VLDB, and CIDR, and has been recognized as a Distinguished Reviewer by multiple venues.
- Data Management
- Data Science
- Databases
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