Dates: 2023
Principal Investigator: Dr. Ayaz ul Hassan Khan
Funded by: SDAIA-KFUPM Joint Research Center for Artificial Intelligence

Description: This project aims to revolutionize weather forecasting by integrating AI, big data analytics, and GPU technology. It focuses on enhancing the CUDA Dataframe (cuDF) to create a GPU-accelerated, distributed framework that makes advanced weather prediction more accurate, efficient, and accessible. The solution targets meteorologists, researchers, and AI developers, simplifying the use of deep learning and large datasets while reducing technical barriers. The framework’s impact spans industries like agriculture, logistics, disaster management, and renewable energy by enabling real-time monitoring, early warnings, and precise long-term forecasts. By democratizing GPU-powered weather prediction—even on standard hardware—the project seeks to deliver scalable, high-performance forecasting tools. Ultimately, it champions a new era of weather prediction marked by improved accuracy, resilience, and accessibility across sectors.