Eva Arias-de-Reyna
Papers
1
Total Citations
28
H-Index
1
About
Eva Arias-de-Reyna is a leading researcher in signal processing and wireless communications, with a primary focus on the Internet of Things (IoT) and spatial field estimation. Her work addresses the critical challenge of inferring physical quantities—such as radio-frequency interference, pollution levels, or temperature—from crowd-sourced data. In her highly cited 2018 paper, "Crowd-Based Learning of Spatial Fields for the Internet of Things: From Harvesting of Data to Inference," she pioneered methods for leveraging distributed, user-collected measurements to build accurate spatial models, enabling context-aware applications. This work, with 28 citations, has become a foundational reference for IoT sensing and inference. Beyond this, her contributions span sensor networks, statistical learning, and resource allocation, with her research consistently bridging theory and practical deployment. Her achievements include advancing the understanding of how to efficiently harvest and process data from heterogeneous sources, making her a key figure in the evolution of intelligent, data-driven wireless systems.
Research Focus
Key Achievements
Top Papers
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