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X-WR-CALDESC:Events for Information Systems Group
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DTSTART:20240310T100000
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DTSTART;TZID=America/Los_Angeles:20240301T130000
DTEND;TZID=America/Los_Angeles:20240301T140000
DTSTAMP:20260421T134114
CREATED:20240228T200048Z
LAST-MODIFIED:20240228T200048Z
UID:1685-1709298000-1709301600@isg.ics.uci.edu
SUMMARY:Yunyan Ding: Efficient Mouse Brain Image Processing Using Collaborative Data Workflows on Texera
DESCRIPTION:Abstract:\nIn 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. In this study\, we introduce a distributed computational pipeline designed for processing high-resolution mouse brain tile images captured by TissueCyte. This pipeline efficiently and accurately stitches these tiles and stacks 2D sections to construct detailed whole mouse brain models in 3D. Our high-quality 3D volumes can facilitate secondary analyses such as whole-brain 3-dimensional registration and segmentation\, cell counting\, and high-resolution volumetric visualization. By utilizing specialized optimization methods within Texera platform to distribute computational resources\, our pipeline achieves an over 80\% reduction in processing times\, enhancing the efficiency significantly. Additionally\, this pipeline is designed with scalability and flexibility\, enabling it to process large volumes of high-resolution neuroimaging data across various computational environments. Our work is developed through a collaborative effort among neuroscience\, computer vision\, and data processing teams\, exemplifying the power of creating tools for interdisciplinary collaboration in addressing complex research challenges.\n\nBio:\nYunyan Ding is a second-year Ph.D. student in the Computer Science Department at UC Irvine. Her research interests include data processing systems and big data analytics.
URL:https://isg.ics.uci.edu/event/yunyan-ding-efficient-mouse-brain-image-processing-using-collaborative-data-workflows-on-texera/
LOCATION:DBH 4011
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BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20240315T130000
DTEND;TZID=America/Los_Angeles:20240315T140000
DTSTAMP:20260421T134114
CREATED:20240311T193926Z
LAST-MODIFIED:20240311T193926Z
UID:1693-1710507600-1710511200@isg.ics.uci.edu
SUMMARY:Yinan Zhou: SpendableDB: A UTxO-based decentralized Database
DESCRIPTION:Abstract: \nBlockchain 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. \nBio: \nYinan 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.
URL:https://isg.ics.uci.edu/event/yinan-zhou-spendabledb-a-utxo-based-decentralized-database/
LOCATION:DBH 4011
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