Maryam Masoumi
Papers
1
Total Citations
2
H-Index
1
About
Maryam Masoumi is a leading researcher at the forefront of next-generation industrial communications, specializing in ultra-reliable low-latency communication (URLLC) and multi-access edge computing (MEC) for Industry X.0. Her work tackles the critical challenge of enabling real-time, high-bandwidth applications—such as augmented and virtual reality (AR/VR), autonomous robotics, and advanced security systems—within complex industrial environments. Masoumi’s major contribution is the development of a quantitative, digital twin-based framework for dynamic MEC resource management, which optimizes network performance by creating virtual replicas of physical systems to predict and allocate resources in real time. This innovative approach, detailed in her 2024 paper, has already garnered 2 citations, signaling its growing influence among peers. By bridging the gap between theoretical network models and practical industrial deployment, Masoumi is shaping the infrastructure for the factories of the future. Her work is essential reading for students and researchers interested in the intersection of IoT, edge intelligence, and digital twins, offering a roadmap for achieving the stringent latency and reliability demands of Industry X.0.
Research Focus
Key Achievements
Top Papers
- 1