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PODCAST

Disseminate: The Computer Science Research Podcast

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

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All Episodes

32:15

Chuzhe Tang | Ad Hoc Transactions in Web...

Disseminate: The Computer Science Research Podcast ·

2022/07/25

Summary: Many transactions in web applications are constructed ad-hoc in the application code. For example, developers might explicitly use locking primitives or validation procedures to coordinate critical code fragments. In this episode, Chuzhe tells us these ad-hoc transactions, database operations coordinated by application code.Until Chuzhe’s work, little was known about them. In this episode he chats about the first comprehensive study on ad hoc transactions. By studying 91 ad hoc transactions

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27:57

Michael Abebe | Proteus: Autonomous Adaptive Storage...

Disseminate: The Computer Science Research Podcast ·

2022/07/18

Summary:Enterprises use distributed database systems to meet the demands of mixed or hybrid transaction/analytical processing (HTAP) workloads that contain both transactional (OLTP) and analytical (OLAP) requests. Distributed HTAP systems typically maintain a complete copy of data in row-oriented storage format that is well-suited for OLTP workloads and a second complete copy in column-oriented storage format optimised for OLAP workloads. Maintaining these data copies consumes significant storage

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32:00

Hani Al-Sayeh | Juggler: Autonomous Cost Optimization...

Disseminate: The Computer Science Research Podcast ·

2022/07/11

Summary:Distributed in-memory processing frameworks accelerate iterative workloads by caching suitable datasets in memory rather than recomputing them in each iteration. Selecting appropriate datasets to cache as well as allocating a suitable cluster configuration for caching these datasets play a crucial role in achieving optimal performance. In practice, both are tedious, time-consuming tasks and are often neglected by end users, who are typically not aware of workload semantics, sizes of

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11:50

Thomas Hütter | JEDI: These aren’t the JSON documents...

Disseminate: The Computer Science Research Podcast ·

2022/07/08

Summary:The JavaScript Object Notation (JSON) is a popular data format used in document stores to natively support semi-structured data.In this interview, Thomas talks about how he addressed the problem of JSON similarity lookup queries: given a query document and a distance threshold, retrieve all documents that are within the threshold from the query document, i.e., get me all similar documents!. Different from other hierarchical formats such as XML, JSON supports both ordered and unordered

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12:06

Sainyam Galhotra | Causal Feature Selection for...

Disseminate: The Computer Science Research Podcast ·

2022/07/08

Summary:The use of machine learning (ML) in high-stakes societal decisions has encouraged the consideration of fairness throughout the ML lifecycle. Although data integration is one of the primary steps to generate high-quality training data, most of the fairness literature ignores this stage. In this interview Sainyam discusses why he focuses on fairness in the integration component of data management, aiming to identify features that improve prediction without adding any bias to the dataset

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17:14

Draco Xu | TSUBASA: Climate Network Construction on...

Disseminate: The Computer Science Research Podcast ·

2022/07/04

Summary: A climate network represents the global climate system by the interactions of a set of anomaly time-series. Network science has been applied on climate data to study the dynamics of a climate network. The core task and first step to enable interactive network science on climate data is the efficient construction and update of a climate network on user-defined time-windows. In this interview Draco talks about TSUBASA, an algorithm for the efficient construction of climate networks based on

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19:21

Felix S Campbell | Efficient Answering of Historical...

Disseminate: The Computer Science Research Podcast ·

2022/07/01

Summary:In this interview Felix discusses "historical what-if queries", a novel type of what-if analysis that determines the effect of a hypothetical change to the transactional history of a database. For example, “how would revenue be affected if we would have charged an additional $6 for shipping?” In his research Felix has developed efficient techniques for answering these historical what-if queries, i.e., determining how a modified history affects the current database state. During the show,

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24:32

Alex Isenko | Where Is My Training Bottleneck? Hidden...

Disseminate: The Computer Science Research Podcast ·

2022/06/27

Summary: Preprocessing pipelines in deep learning aim to provide sufficient data throughput to keep the training processes busy. Maximizing resource utilization is becoming more challenging as the throughput of training processes increases with hardware innovations (e.g., faster GPUs, TPUs, and inter-connects) and advanced parallelization techniques that yield better scalability. At the same time, the amount of training data needed in order to train increasingly complex models is growing. As a

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1:30

Coming Soon | ACM SIGMOD/PODS 2022 | #0

Disseminate: The Computer Science Research Podcast ·

2022/06/03

Welcome to Disseminate! The podcast bringing you the cutting edge of Computer Science research in a digestible format. Each series will focus on papers published at a specific Computer Science conference, e.g., SIGMOD, CVPR, so we will cover a wide range of topics from distributed systems to computer vision. Each episode within a series will feature an interview with the author(s) of a paper published at that conference. The podcasts aims to be an alternative source of information for industry

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