Michael J. Franklin – Data Science Trends and Non-Trends: A Confluence of Complexity

Abstract

The field of Data Science continues to expand in scope, scale and importance. New flexible data architectures are reducing the friction for collecting, managing and accessing data. Open data standards and cloud computing are enabling rapid innovation leading to new products and entire new product categories. ML and AI are finally showing their ability to solve problems for non-expert users across many fields. This expansion brings the potential for increased value, but also brings with it an increase in the intricacy of data environments in terms of performance, accuracy, explainability, and management. This talk will survey several of these trends and discuss their implications for users as well as for those of us who are developing educational and research programs in this fast moving landscape.

Prof. Michael J. Franklin
(University of Chicago)

MICHAEL J. FRANKLIN is the Liew Family Chair of Computer Science and Sr. Advisor to the Provost for Computation and Data Science at the University of Chicago where he also serves as Faculty Co-Director of the Data Science Institute. Previously he was Thomas M. Siebel Professor of Computer Science at the University of California, Berkeley and served a term as Chair of the Computer Science Division. He was Co-Director of the Algorithms, Machines and People Laboratory (AMPLab) and is one of the original creators of Apache Spark, a leading open source platform for advanced data analytics and machine learning that was initially developed 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 received the 2022 ACM SIGMOD Systems Award with the team that developed Spark, and is a two-time recipient of the ACM SIGMOD “Test of Time” award. He holds a Ph.D. from the Univ. of Wisconsin (1993).