Nerea Aranjuelo
Papers
1
Total Citations
7
H-Index
1
About
Nerea Aranjuelo is a researcher at the forefront of edge AI and computer vision, specializing in the efficient deployment of deep neural networks (DNNs) across heterogeneous Internet of Things (IoT) platforms. Her work addresses the critical challenge of running computationally intensive face recognition (FR) solutions on resource-constrained devices such as robots, tablets, and smartphones. In her most-cited paper, "Designing Automated Deployment Strategies of Face Recognition Solutions in Heterogeneous IoT Platforms" (2021, 7 citations), Aranjuelo proposes novel strategies to optimize DNN deployment while balancing performance, security, and energy efficiency. This contribution is vital for enabling real-time, privacy-preserving AI in distributed environments. Her research bridges the gap between high-accuracy models and practical edge deployment, making her a key figure in the evolution of smart, autonomous systems. With a focus on automation and scalability, Aranjuelo's work empowers next-generation IoT applications, from smart surveillance to interactive robotics, and continues to influence the design of robust, adaptive AI solutions for the real world.
Research Focus
Key Achievements
Top Papers
- 1