Papers

20

Total Citations

221

H-Index

7

About

Mounir Ghogho is a prominent researcher whose work sits at the dynamic intersection of wireless communications, robotics, and artificial intelligence. His most significant contributions lie in the emerging field of communications-aware robotics — a discipline exploring how mobile robots and unmanned aerial vehicles (UAVs) can optimize their behavior in response to wireless channel conditions. Ghogho's pioneering work on mobility diversity, introduced around 2016, demonstrated how robots could intelligently exploit controlled movement to combat wireless fading and maximize energy harvesting, a concept he has since extended to trajectory planning under real-world channel uncertainty. His research has garnered substantial recognition, with a survey on deep learning techniques for Visual SLAM alone accumulating 71 citations, reflecting its value to the robotics and computer vision communities. Beyond communications-aware navigation, Ghogho has explored physical layer security using omnidirectional aerial vehicles and, most recently, personalized vision-language models for human-robot interaction. His tutorial and survey contributions serve as essential entry points for researchers entering these fields. Collectively, his work bridges theoretical wireless communications with practical autonomous systems, making him a distinctive and influential voice shaping the future of intelligent, communication-enabled robotics.

Research Focus

Key Achievements

7
H-Index
20
Papers
221
Total Citations
11
Avg Citations/Paper
🏆 Most Cited Paper
Deep Learning Techniques for Visual SLAM: A Survey
71 citations · 2023
📈 Most Prolific Year: 2019 (3 Papers)
🤝 Key Collaborators: 18
🏛 Institutions: University of Leeds, International University of Rabat, Université Mohammed VI Polytechnique

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago