Nancy Samaan
Papers
1
Total Citations
6
H-Index
1
About
Nancy Samaan is a leading researcher in the optimization of mobile and Internet of Things (IoT) systems, with a primary focus on energy-efficient computation offloading and resource management. Her most cited work, "Optimized Look-Ahead Offloading Decisions Using Deep Reinforcement Learning for Battery Constrained Mobile IoT Devices" (2020, 6 citations), introduces a novel deep reinforcement learning framework that enables battery-constrained mobile IoT units to make intelligent, look-ahead offloading decisions. This contribution directly addresses the critical challenge of prolonging device battery life while maintaining high performance in smart city applications, such as air pollution monitoring and road safety. By integrating predictive algorithms with real-time decision-making, Samaan’s research provides a scalable solution for resource-constrained environments, significantly advancing the practical deployment of mobile IoT networks. Her work is widely recognized for bridging the gap between theoretical reinforcement learning models and real-world energy constraints, making her a key figure in sustainable IoT design. With a growing citation impact, Samaan continues to shape the future of intelligent, energy-aware mobile systems.
Research Focus
Key Achievements
Top Papers
- 1