Sabah M. Alzahrani
Papers
1
Total Citations
3
H-Index
1
About
Sabah M. Alzahrani’s research lies at the intersection of robotics, cloud computing, and artificial intelligence, with a focus on optimizing data offloading and computational efficiency. Her most-cited work, "Markov decision process with deep reinforcement learning for robotics data offloading in cloud network" (2022), addresses a critical challenge: robots often lack the processing power, memory, and energy to run complex programs locally. By integrating cloud computing with deep reinforcement learning, she developed a decision-making framework that enables robots to offload tasks intelligently, balancing latency and resource use. This contribution has garnered 3 citations and highlights her ability to merge theoretical models with practical robotics applications. Alzahrani’s work is notable for advancing edge-cloud collaboration, making autonomous systems more capable and energy-efficient. Her research is particularly relevant for students and engineers exploring how AI can bridge hardware limitations in robotics, offering a pathway to scalable, real-time performance in cloud-connected networks.
Research Focus
Key Achievements
Top Papers
- 1