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Chicago Data Night is a monthly speaker series co-hosted by the Data Science Institute, ChiData, and Drive Capital. The event brings together the analytical rigor of academia with the practical insights of industry professionals to unlock new pathways for discovery and development with the broader community.

“Collaboration between industry and academia is essential for driving innovation and addressing real-world challenges. Events like Chicago Data Night create invaluable opportunities for us to exchange ideas, share insights, and explore the practical applications of our research. Together, we can bridge the gap between theory and practice, ensuring that our work has a meaningful impact on both sectors.” Raul Castro Fernandez, ChiData Lead and event organizer.

Register to attend our next Chicago Data Night, take a look at past Chicago Data Nights below, and look out for future events on the DSI Events page.

Data Night Co-Organizers

Anne brings a history of successful corporate engagement, strategic partnerships, and nonprofit leadership to her role as Director of Corporate Partnerships at the Data Science Institute. Anne previously served as a national program manager at the American Red Cross. There, she led several high-impact initiatives, including the Annual Disaster Giving Program, where she successfully partnered with over 150 top corporations to advance the organization’s disaster relief efforts.

Anne’s experience extends beyond national borders, having served as an international strategic advisor, where she worked closely with sister Red Cross Societies to craft and implement comprehensive resource mobilization strategies. Before her work at the Red Cross, she served on the Development team at Equal Justice Works, a nonprofit dedicated to creating a sustainable pathway for recent law graduates to enter public interest law.

Anne also holds a master’s degree in public policy from the Harris School at the University of Chicago.

Raul Castro Fernandez is an Assistant Professor of Computer Science at the University of Chicago. In his research he builds systems for discovering, preparing, and processing data. The goal of his research is to understand and exploit the value of data. He often uses techniques from data management, statistics, and machine learning. His main effort these days is on building platforms to support markets of data. This is part of a larger research effort on understanding the Economics of Data. He is the faculty co-lead of the DSI’s Data Ecology Research Initiative and he is part of ChiData, the data systems research group at the University of Chicago.

Chris Zhu is currently a Computer Science PhD student at the University of Chicago, advised by Professor Raul Castro Fernandez. He is broadly interested in data systems, and currently working on Data Station, a system for enabling data sharing. Before his doctoral studies, Chris earned a bachelor’s degree in Computer Science from the University of Chicago.

Past Events

Arjun Ravi Kannan (Discover Financial Services)

The Use of Responsible AI in a Regulated Industry

Becca Taft (Cockroach Labs)

CockroachDB: The Resilient Geo-Distributed SQL Database

Sanjay Krishnan (EchoMark)

Combating Knowledge-Based Threats in an Evolving Cybersecurity Landscape

James Nowell (EZ Bot AI)

Events as a Data Quanta: How Thinking with Events and DDD (Domain-Driven Design) will make you a Stronger Data User

Neal Sample (Walgreens Boots Alliance)

Why Asking the Right Questions Matters More Than Having All the Answers

Dexter Horthy (Metalytics)

OSS tools for understanding the value of your data

Aramide Kehinde (Amazon Web Services)

Create results through real life scenarios in Media & Entertainment, and Health & Wellbeing

David Zaretsky, PhD (Northwestern)

BIG AI + BIG IDEAS: The Future of Innovation, Entrepreneurship and AI

Douglas Laney (Infonomics)

Data is NOT the New Oil (Hint: It’s far more valuable)

Raul Castro Fernandez (UChicago Data Science)

Data Ecology, Data Markets, the Value of Data, and Dataflow Governance

Ari Kaplan (Databricks)

Business Trends: Building Data & AI at Scale and Velocity
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