This podcast features interviews with Computer Science researchers. Hosted by Dr. Jack Waudby researchers are interviewed, highlighting the problem(s) they tackled, solutions they developed, and how their findings can be applied in practice. This podcast is for industry practitioners, researchers, and students, aims to further narrow the gap between research and practice, and to generally make awesome Computer Science research more accessible. We have 2 types of episode: (i) Cutting Edge (red/blue logo) where we talk to researchers about their latest work, and (ii) High Impact (gold/silver logo) where we talk to researchers about their influential work.
You can support the show through Buy Me a Coffee. A donation of $3 will help us keep making you awesome Computer Science research podcasts.
Hosted on Acast. See acast.com/privacy for more information.
This podcast features interviews with Computer Science researchers. Hosted by Dr. Jack Waudby researchers are interviewed, highlighting the problem(s) they tackled, solutions they developed, and how their findings can be applied in practice. This podcast is for industry practitioners, researchers, and students, aims to further narrow the gap between research and practice, and to generally make awesome Computer Science research more accessible. We have 2 types of episode: (i) Cutting Edge (red/blue logo) where we talk to researchers about their latest work, and (ii) High Impact (gold/silver logo) where we talk to researchers about their influential work.
You can support the show through Buy Me a Coffee. A donation of $3 will help us keep making you awesome Computer Science research podcasts.
Hosted on Acast. See acast.com/privacy for more information.
In this episode we kick off our DuckDB in Research series with Till Döhmen, a software engineer at MotherDuck, where he leads AI efforts. Till shares insights into DuckDQ, a Python library designed for efficient data quality validation in machine learning pipelines, leveraging DuckDB’s high-performance querying capabilities.
We discuss the challenges of ensuring data integrity in ML workflows, the inefficiencies of existing solutions, and how DuckDQ provides a lightweight, drop-in replacement that seamlessly integrates with scikit-learn. Till also reflects on his research journey, the impact of DuckDB’s optimizations, and the future potential of data quality tooling. Plus, we explore how AI tools like ChatGPT are reshaping research and productivity. Tune in for a deep dive into the intersection of databases, machine learning, and data validation!
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