Papers
9
Total Citations
417
H-Index
7
About
Mahbuba Afrin is a leading researcher at the intersection of cloud robotics, edge computing, and cyber-physical systems (CPS). Her work focuses on solving critical challenges in resource allocation, task offloading, and system resilience for multi-agent robotic networks. Afrin’s major contributions include pioneering multi-objective optimization frameworks that balance energy consumption, delay, and computational load in smart factories and agricultural CPS. Her comprehensive survey on resource provisioning in multi-agent cloud robotics (165 citations) has become a foundational reference in the field. She has also advanced deep reinforcement learning techniques for dynamic task allocation, ensuring robotic edge systems remain resilient under uncertain failures. Her research spans latency-sensitive applications in Industry 4.0, healthcare, and disaster management, where she has developed novel architectures like Fog-Dew infrastructure and UAV-as-a-Service for robust operations. With over 400 cumulative citations and a consistent record of high-impact publications from 2018 to 2025, Afrin is recognized for shaping the future of Internet of Robotic Things (IoRT) through energy-efficient, resilient, and intelligent robotic ecosystems.
Research Focus
Key Achievements
Top Papers
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- 3Robotic Edge Resource Allocation for Agricultural Cyber-Physical System36 citations · 2021
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- 9UAV-as-a-Service for Robotic Edge System Resilience3 citations · 2024