ISG Talks are sponsored by Couchbase.
Yunyan Ding: Efficient Mouse Brain Image Processing Using Collaborative Data Workflows on Texera
DBH 4011Abstract: In the field of neuroscience, accurately mapping the complex three-dimensional (3D) neural circuitry and architecture of the brain is crucial for advancing our understanding of brain functions and disorders. […]
Bratin Saha (AWS Amazon): Scaling Generative AI in the Enterprise
DBH 4011Abstract: Machine learning (ML) and generative artificial intelligence (AI) is one of the most transformational technologies that is opening up new opportunities for innovation in every domain across software, finance, […]
Yinan Zhou: SpendableDB: A UTxO-based decentralized Database
DBH 4011Abstract: Blockchain technology has attracted a significant amount of attention ever since the Bitcoin blockchain's success. Currently, most of the research and engineering efforts have been centered around monetary transactions such as token exchange protocols. The potential of building databases on top of blockchains is largely overlooked and remains an open problem. The literature on blockchain databases is divided into permissioned blockchains and permissionless account-based blockchains. However, the former is not fully decentralized, and the latter suffers from challenges in performance and cost. We propose SpendableDB, a permissionless UTxO-based blockchain database as a novel approach to the problem of data decentralization. Our design integrates data into individual UTxOs to achieve true decentralization of data ownership that can be securely transferred and traded, similar to how the regular monetary UTxOs are protected by the underlying blockchain's decentralization protocol. Additionally, SpendableDB provides cryptographically secured data integrity and immutable data lineage that can be easily verified. Our implementation and experiments show that our design is economically practical as it incurs a small amount of blockchain transaction fees. Bio: Yinan Zhou is a second-year Ph.D. student in the Computer Science Department at UC Irvine. His primary research focus is on blockchain infrastructure and application developments.
Lukasz Golab (University of Waterloo): Understanding models and the data they learn from
DBH 4011Lukasz Golab (U. Waterloo) Understanding models and the data they learn from Abstract: The modern world is powered by data. However, as the capabilities of data-intensive systems grow, so does […]
Juncheng Fang: ImmortalChopper: Real-Time and Resilient Distributed Transactions in the Edge-Cloud
DBH 4011Abstract: Emerging applications in the areas of real-time Internet of Things (IoT) and edge technologies (such as wearables, and mobile headsets) require fast processing and response times. This motivates the […]
Mohammed Al-Kateb (Amazon Redshift): The Evolution of Amazon Redshift
DBH 4011Abstract: In this talk, we will discuss the evolution of Amazon Redshift over the past 10 years. We’ll discuss the Amazon Redshift architecture. We’ll dive deep in the lifecycle of […]
Xinyuan Lin: Data Science Tasks Implemented with Scripts versus GUI-Based Workflows: The Good, the Bad, and the Ugly.
DBH 4011Abstract: As leveraging large-scale data analytics becomes the norm for many applications, platforms for developing these capabilities have become increasingly important. This work compares the benefits and drawbacks of implementing […]
Mike Heddes: Efficient Cardinality Estimation of Multi-Join Queries using Count Sketches
DBH 4011Abstract: Cardinality estimates are a primary input to query optimizers to determine an appropriate join order. The seminal AMS sketch can estimate the cardinality of an equi-join between two relations […]
Pat Helland (Salesforce): Scalable OLTP in the Cloud: What’s the BIG DEAL?
DBH 4011Abstract: The pursuit of scalable OLTP systems has been the holy grail of my career. Because OLTP systems are typically split into applications and databases, the isolation semantics provided by […]
Mohammad Sadoghi (UC Davis): The Journey of Building Global-Scale Sustainable Blockchain Fabric
DBH 6011Abstract The inception of Bitcoin and blockchain has renewed the vision of a democratic and decentralized computational paradigm, that is, to ingrain integrity, transparency, and accountability into the very fabric […]
Aditya Parameswaran (Berkeley): Enhance, Don’t Replace: A Recipe for Success in Data Tooling
DBH 6011Enhance, Don't Replace: A Recipe for Success in Data Tooling Abstract: Most data analysis and data science is performed in human-centered tools, such as spreadsheets, visual analytics tools, and data science […]
Arnab Nandi (OSU): Data Exploration in a Camera-first World: Query and Result Challenges
DBH 4011Prof. Arnab Nandi Associate Professor, Computer Science and Engineering The Ohio State University Friday, October 11, 2024 at 11 a.m. Donald Bren Hall 6011 Title: "Data Exploration in a Camera-first […]
Nika Mansouri Ghiasi (ETH): Storage-Centric Computing for Genomics and Metagenomics
DBH 4011Title: Storage-Centric Computing for Genomics and Metagenomics Abstract Genomics and metagenomics applications have enabled significant advancements in many critical areas. The exponential growth of genomic data poses unprecedented challenges in […]
Yannis Papakonstantinou (Google): Vector Search and Databases
DBH 6011Yannis Papakonstantinou Distinguished Engineer, Query Processing and GenAI at Google Cloud Databases Abstract: Semantic search ability, via embedding (vectors) and vector indexing, has been added to Google Cloud Platform (GCP) […]
Michael Jungmair (TU Munich): A Compiler-Centric Query Engine Design for Mixed Workloads and Modern Hardware
DBH 3011A Compiler-Centric Query Engine Design for Mixed Workloads and Modern Hardware 11/1/2024, 1:00 PM 2 PM, DBH 3011 Michael Jungmair, Technical University of Munich, Germany Abstract: Relational query engines are increasingly expected to handle more than just relational queries and also run on modern hardware that is increasingly parallel and distributed. However, it is not clear how existing system designs can deal with these two challenges effectively. We propose a holistic, compiler-centric design for data processing systems that is designed for tightly integrated optimization and execution of relational queries, non-relational workloads and user-defined functions on modern hardware. Bio: Michael Jungmair is a third year PhD student at the Technical University of Munich. Supervised by Jana Giceva, he is performing research in the intersection of database engines and compiler technology. So far, this research culminated in the design and implementation of LingoDB (lingo-db.com), a novel query engine based on the MLIR compiler framework