Sirine Bouhoula
Papers
1
Total Citations
3
H-Index
1
About
Sirine Bouhoula is a rising researcher at the forefront of Mobile Edge Computing (MEC) and Edge Robotics, where she tackles the critical challenge of enabling real-time, autonomous decision-making at the network edge. Her most cited work, “DRL-based Trajectory Planning and Sensor Task Scheduling for Edge Robotics” (2024), introduces a deep reinforcement learning framework that dynamically optimizes robot trajectories and sensor scheduling under highly mobile conditions—a key bottleneck for industrial automation. By addressing the inherent unpredictability of edge environments, Bouhoula’s contributions bridge the gap between theoretical MEC models and practical, latency-sensitive robotic applications. Though early in her career, her work has already garnered attention (3 citations), signaling its relevance to both academia and industry. Her research promises to unlock new levels of efficiency in smart manufacturing, autonomous logistics, and real-time edge intelligence, positioning her as a promising voice in the next wave of edge-native robotics.
Research Focus
Key Achievements
Top Papers
- 1