Presentation
NetCDFaster: A Geospatial Cyberinfrastructure Enhancing Multi-Dimensional Scientific Dataset Access and Visualization Through Machine Learning Optimization
DescriptionThis project introduces an enhanced solution for accessing and processing NetCDF data, a widely used standard in geosciences for storing multidimensional data. Existing tools often compromise on performance or lack full workflow support. The proposed system integrates machine learning, specifically a CatBoost classifier, with a modern web application to improve the speed and accuracy of data querying and visualization. It provides a user-friendly interface for uploading NetCDF files and extracting metadata efficiently. Experimental results demonstrate a 64% F1-score in selecting optimal parameters and up to 80% improvement in processing time, significantly aiding scientific analysis.
Event Type
ACM Student Research Competition: Graduate Poster
ACM Student Research Competition: Undergraduate Poster
Doctoral Showcase
Posters
TimeTuesday, 19 November 202412pm - 5pm EST
LocationB302-B305