About

Hakim Mabed is a researcher specializing in distributed algorithms, micro-robotics, and nanonetworks, with particular expertise in the coordination and self-reconfiguration of large-scale robotic systems. His work sits at the intersection of programmable materials, modular robotics, and wireless network design, tackling some of the most demanding computational challenges posed by miniaturized, resource-constrained devices. Mabed's most significant contributions center on developing scalable, map-less self-reconfiguration algorithms for MEMS micro-robots — systems where memory, energy, and processing power are severely limited. His foundational papers from 2012 to 2014 established distributed, dynamic frameworks allowing swarms of micro-robots to autonomously reshape and redeploy without centralized control, earning consistent recognition across the community. His 2016 work on modular micro-robot network reorganization and his shape-shifting algorithm research further advanced the field of programmable matter, a concept with far-reaching implications in medicine, manufacturing, and adaptive structures. More recently, Mabed has extended his expertise into terahertz nanonetworks and ultra-dense routing protocols, addressing connectivity challenges in next-generation nano-scale communication systems. With cumulative citations across ten notable publications, his body of work represents a cohesive and growing contribution to autonomous distributed systems and the emerging frontier of nanoscale networking.

Research Focus

Key Achievements

6
H-Index
12
Papers
71
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
Scalable Distributed Protocol for Modular Micro-Robots Network Reorganization
10 citations · 2016
📈 Most Prolific Year: 2014 (4 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: Franche-Comté Électronique Mécanique Thermique et Optique - Sciences et Technologies, Centre National de la Recherche Scientifique, Université de franche-comté, Université Bourgogne Franche-Comté, L'Hôpital Nord Franche-Comté

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago