Associate Professor
4128 Multidisciplinary Research Building (MRB1)
Computer Science and Engineering
University of California, Riverside
Ahmed Eldawy is an Associate Professor in 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 led the research and development in many open source projects for big spatial data exploration and visualization including UCR-Star, an interactive repository for geospatial data with nearly four terabytes of publicly available data. He is a recipient of the highly prestigious NSF CAREER award as well as the best demo award in SIGSPATIAL 2020. His work is supported by the National Science Foundation (NSF) and the US Department of Agriculture (USDA).
$1.2 Million NSF grant to process Big Low-Value
Data ... more
$10 Million USDA NIFA grant
to to support sustainable agriculture using AI ...
more
NSF - IIS-2046236 - CAREER: Towards Exploratory Data Science on Spatio-temporal Big Data
Total amount: $543,135
From 10/01/2021 to 09/30/2026
USDA NIFA - 2020-69012-31914 - Artificial Intelligence for Sustainable Water, Nutrient, Salinity, and Pest
Management in the Western U.S.
Total amount: $10,000,000 (PI share: $636,393)
From 9/01/2020 - 8/31/2025
University of California Office of the President - M21PL3368 - California Informatics for Equitable Disaster
Response and Recovery
Total amount: $262,428 (PI Share: $62,300)
From 01/01/2021 to 12/31/2022
NSF - IIS-1954644 - III: Medium: Collaborative Research: Supporting High-Value Analytics on Big Low-Value Data
Total amount: $1,200,000 (PI share: $304,766)
From 10/01/2020 - 9/30/2023
NSF - CNS-1924694 - CCRI: ENS: Collaborative Research: Supporting and Sustaining Apache AsterixDB for the CISE
Research Community
Total amount: $2,000,000 (PI share: $302,950)
From 9/01/2019 - 8/31/2022
NSF - IIS-1838222 - BIGDATA: F: Collaborative Research: Optimizing LSM-Based Big Data Management Systems
Total amount: $2,000,000 (PI share: $426,614)
From 1/01/2019 - 12/31/2022
USDA AFRI-AST - 2019-67022-29696 - Agricultural Salinity Management Via An Integration Of Proximal And Remote
Sensing With Big Geodata Modeling
Total amount: $487,943 (PI share: $128,572)
From 7/01/2019 - 6/30/2022
Beast is a system for Big Exploratory Analytics on Spatio-temporal data. It adds many Spark-based functions for loading, indexing, analyzing, visualizing, and summarizing big spatio-temporal data. UCR-Star is one example of a system that is built using Beast.
UCR STAR the spatio-temporal active repository that hosts terabytes of public geospatial data in an interactive repository. The main goal is to allow the researchers worldwide to unleash the true value of the datasets that are available all over the web. We encourage the community to submit their requests to add new datasets to UCR-Star and we will be process them.
Raptor is the Raster+Vector query processing engine built in Spark. Raptor is designed to efficiently combine raster data, e.g., satellite images, with vector data, e.g., roads and boundaries, in one efficient query processing core. Raptor has already been applied in many scientific applications including crop yield estimation and combating wild fires.
Spider is a web-based spatial data generator that aims at making synthetic datasets easier to generate, visualize, and share. With Spider, you can generate billions of records of synthetic data and share them with your project members with a simple web link.
I am an accredited Scientific Teaching Fellow by Yale Center for Teaching and Learning sponsored by the National Science Foundation.
