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Events for the 4th week of October
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CS Colloquium: Ahmed Eldawy (University of California, Riverside) - Interactive Data Exploration as a Service
Tue, Oct 22, 2019 @ 03:30 PM - 04:50 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Ahmed Eldawy, University of California, Riverside
Talk Title: Interactive Data Exploration as a Service
Series: Computer Science Colloquium
Abstract: Recently, there has been a tremendous growth in data collection from various sources such as satellites, IoT sensors, smartphones, autonomous cars, and others. At the same time, there is a move for open data led by governments, non-profit organizations, and industry which makes hundreds of thousands of datasets publicly available. This abundance of publicly available open data led to the new data revolution where everyone is interested in exploring this data to look for interesting patterns and innovative findings. While computer scientists and data scientists know how to process this data, no one is out to help citizen scientists, those with little to no knowledge about programming and data management.
This talk describes a new approach to provide citizen scientists with interactive data exploration as a service (IDEAS). The goal is to allow anyone to start exploring those publicly available datasets without a costly process of installing and learning data processing tools or even downloading the datasets of interest. This system will act as an ice breaker that will help engaging more citizen scientists into the field of data science. The main challenge is how to provide real-time processing for hundreds of thousands and petabytes of datasets through a simple interface. This talk describes three modules related to this system, synoptic computation, incremental indexing, and interactive visualization. The synoptic computation module scales up the query processing by providing a real-time approximate answer over small-size synopses of the data such as samples and histograms. The incremental indexing module works in the background and incrementally organizes the data over a cluster of machines to speed up the query processing. Finally, the interactive visualization module presents the results in a visual format which allows the users to inspect the query answers. Preliminary results on the proposed system show that it can bridge the gap between the user requirements for interactivity and the increasing volume of big spatial data.
This lecture satisfies requirements for CSCI 591: Research Colloquium.
Biography: Ahmed Eldawy is an Assistant Professor of Computer Science at the University of California, Riverside. His research interests lie in the broad area of databases with a focus on big data management and spatial data processing. Ahmed is the main inventor of SpatialHadoop, the most comprehensive open source system for big spatial data management. Ahmed has many collaborators in industrial research labs including Microsoft Research and IBM Watson. He was awarded the Quality Metrics Fellowship in 2016, Doctoral Dissertation Fellowship in 2015, and Best Poster Runner-up award in ICDE 2014. His work is supported by the National Science Foundation (NSF) and the US Department of Agriculture (USDA).
Host: Shahram Ghandeharizadeh
Location: Henry Salvatori Computer Science Center (SAL) - 101
Audiences: Everyone Is Invited
Contact: Computer Science Department
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PhD Defense - Abdullah Alfarrarjeh
Wed, Oct 23, 2019 @ 10:00 AM - 12:00 PM
Thomas Lord Department of Computer Science
University Calendar
PhD Candidate: Abdullah Alfarrarjeh
Committee:
Cyrus Shahabi (chair)
Aiichiro Nakano
C.-C. Jay Kuo
Location: PHE 325
Time: October 23rd, 10 am.
Title: Enabling Spatial-Visual Search for Geospatial Image Databases
Abstract:
Due to continuous advances in camera technologies as well as camera-enabled devices (e.g., CCTV, smartphone, vehicle blackbox, and GoPro), urban streets have been documented by massive amounts of images. Moreover, nowadays, images are typically tagged with spatial metadata due to various sensors (e.g., GPS and digital compass) attached to or embedded in cameras. Such images are known as geo-tagged images. The availability of such geographical context of images enables emerging several image-based smart city applications. Developing such smart city applications requires searching for images, among the massive amounts of collected images, especially to be used for training various machine learning algorithms. Thus, there is an immense need for a data management system for geo-tagged images.
Towards this end, it is paramount to build a data management system that organizes the images in structures that enable searching and retrieving the images efficiently and accurately. On one hand, the data management system should overcome the challenge of lacking an accurate spatial representation of legacy images that were collected without spatial metadata, as well as representing the content of an image accurately using an enriched visual descriptor. On the other hand, the system should also enable efficient storage of images utilizing both their spatial and visual properties and thus their retrieval based on spatial-visual queries. To address these challenges we present a system which includes three integrated modules: a) modeling an image spatially by its scene location using a data-centric approach, b) extending the visual representation of an image with the feature set of multiple similar images located in its vicinity, and c) designing index structures that expedite the evaluation of spatial-visual queries.
Location: 325
Audiences: Everyone Is Invited
Contact: Lizsl De Leon
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Theory Lunch
Thu, Oct 24, 2019 @ 12:15 PM - 02:00 PM
Thomas Lord Department of Computer Science
Conferences, Lectures, & Seminars
Speaker: Prithviraj Prabhu, Graduate Students at USC
Talk Title: Google's Recent Attempts in Quantum Supremacy
Abstract: A talk about Goolge' s recent attempts in quantum supremacy and the controversy surrounding it.
Host: Shaddin Dughmi
Location: Henry Salvatori Computer Science Center (SAL) - 213
Audiences: Everyone Is Invited
Contact: Cherie Carter
