High Impact in Databases with... Andreas Kipf

In this High Impact episode we talk to Andreas Kipf about his work on "Learned Cardinalities".

Andreas is the Professor of Data Systems at Technische Universität Nürnberg (UTN). Tune in to hear Andreas's story and learn about some of his most impactful work.

The podcast is proudly sponsored by Pometry the developers behind Raphtory, the open source temporal graph analytics engine for Python and Rust.

Papers mentioned on this episode:

• Learned Cardinalities: Estimating Correlated Joins with Deep Learning CIDR'19
• The Case for Learned Index Structures SIGMOD'18
• Adaptive Optimization of Very Large Join Queries SIGMOD'18

You can find Andreas on:

• Twitter
• LinkedIn
• Google Scholar
• Data Systems Lab @ UTN

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