Interviews with Computer Science researchers about their latest work. Hosted by 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. Each series focuses on a different Computer Science conference.
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Summary: Federated Learning (FL) enables distributed training by learners using local data, thereby enhancing privacy and reducing communication. However, it presents numerous challenges relating to the heterogeneity of the data distribution, device capabilities, and participant availability as dep...
Summary: Log-structured merge (LSM) trees have emerged as one of the most commonly used storage-based data structures in modern data systems as they offer high throughput for writes and good utilization of storage space. In this episode, Subhadeep Sarkar presents the fundamental principles of the L...
Summary: The increasing need for data trading across businesses nowadays has created a demand for data marketplaces. However, despite the intentions of both data providers and consumers, today’s data marketplaces remain mere data catalogs. In this episode, Andra tells us about her vision for market...
Summary: Sorting is one of the most well-studied problems in computer science and a vital operation for relational database systems. Despite this, little research has been published on implementing an efficient relational sorting operator. In this episode, Laurens Kuiper tells us about his work fil...
Summary: In this episode Semih Salihoğlu tell us about Kùzu, an in-process property graph database management system built for query speed and scalability. Listen to hear the vision for Kùzu and to learn more about Kùzu's factorized query processor! Links: Kùzu GitHub repo CIDR paper contact@kuzudb...