Uday Yatnalli

Papers

Total Citations

167

H-Index

About

Uday Yatnalli is a researcher at the forefront of wireless communications and autonomous aerial systems, with a particular focus on integrating unmanned aerial vehicles (UAVs) into next-generation networks. His most impactful work, "Learning radio maps for UAV-aided wireless networks: A segmented regression approach" (2017), has garnered 167 citations and addresses a critical challenge in the field: enabling communication-enabled drones to autonomously navigate and position themselves as flying wireless relays. By developing a segmented regression framework to construct accurate radio environment maps, Yatnalli’s research provides a foundational tool for UAVs to intelligently fill coverage and capacity gaps in terrestrial networks. This work not only advances the theoretical understanding of aerial-assisted communications but also has practical implications for disaster response, rural connectivity, and dynamic spectrum management. Yatnalli’s contributions stand out for their blend of machine learning, signal processing, and robotics, offering a compelling pathway toward truly autonomous and adaptive wireless infrastructure.