Wednesday / CS Distinguished Lecture

December 4th / 12:00 PM

Hybrid / Mudd 3514

Speaker

Michael Franklin, University of Chicago

Talk Title

Enabling Diverse and Interconnected Data Ecosystems with Lakehouses, Open Formats and AI

Abstract

Data and AI are driving innovation across industry, science and society. At the same time, data management technology has changed dramatically, due a combination of factors such as cloud-based data lakes, the development of open standards for data formats and catalogs, and the opportunities presented by generative AI and other AI technologies. The result of all of these changes is an increasingly vibrant data ecosystem that has the potential to span traditional information silos and data incompatibilities to enable people and organizations to leverage all of their data in ways that have until now, simply have not been possible. In this talk I'll survey this new landscape and give an overview of some of the (to my mind) most promising directions for research and innovation in this rapidly advancing area.

Biography

MICHAEL J. FRANKLIN is the Morton D. Hull Distinguished Service Professor of Computer Science and Founding Faculty Co-Director of the Data Science Institute at the University of Chicago. He is also a Founding Advisor and Visiting Researcher at Databricks, Inc. At Chicago he served as Liew Family Chair of Computer Science, overseeing the department's rapid expansion in scope and stature. Previously he was the Thomas M. Siebel Professor of Computer Science at UC Berkeley where he directed the Algorithms, Machines and People Laboratory (AMPLab), and was part of the original team building Apache Spark, a popular open source data processing framework initiated at the lab. He is a Member of the American Academy of Arts and Sciences and is a Fellow of the ACM and the American Association for the Advancement of Science. He has served on the Board of the Computing Research Association and the NSF CISE Advisory Committee as well as the ACM Fellows Selection Committee. He received the 2022 ACM SIGMOD Systems Award, and is a two-time recipient of the ACM SIGMOD "Test of Time" award. He holds a Ph.D. in Computer Sciences from the Univ. of Wisconsin (1993).

Research/Interest Areas: Data systems, Data Science, Systems and AI/ML, Data Markets

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Zoom: https://northwestern.zoom.us/j/92065267938

Panopto: https://northwestern.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=4eaec4b2-647d-4fba-8b8c-b22701674df8

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