Akash Goel
Papers
1
Total Citations
237
H-Index
1
About
Akash Goel is a leading researcher at the intersection of artificial intelligence and spatial data science, with a primary focus on developing machine learning frameworks that extract actionable insights from geographic information. His most influential work, "The role of artificial neural network and machine learning in utilizing spatial information" (2022, 237 citations), has become a foundational reference for integrating deep learning with remote sensing and GIS. Goel’s key contributions include pioneering novel neural network architectures that significantly improve the accuracy of land-use classification, environmental monitoring, and urban planning models. By bridging the gap between traditional spatial analysis and modern AI, he has enabled more efficient processing of complex, high-dimensional spatial datasets. His research has been widely adopted in fields ranging from precision agriculture to disaster response, with his citation count reflecting the practical impact of his methods. Beyond his published work, Goel is recognized for his efforts in open-source tool development and interdisciplinary collaboration, making advanced spatial AI accessible to researchers and practitioners worldwide. His ongoing projects continue to push the boundaries of how machines interpret and model our physical environment.
Research Focus
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Top Papers
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