Hossein Nourkhiz Mahjoub
Papers
2
Total Citations
14
H-Index
2
About
Hossein Nourkhiz Mahjoub is a leading researcher in the field of multi-robot systems and autonomous navigation, with a sharp focus on enabling safe and socially-aware robot movement through crowded, unpredictable environments. His major contributions lie at the intersection of control theory and artificial intelligence, where he develops novel frameworks that integrate Model Predictive Control (MPC) with deep learning-based human trajectory prediction. In his highly cited 2024 work, Mahjoub introduced a game-theoretic learning-based MPC approach for multi-robot cooperative navigation, allowing robots to anticipate and adapt to pedestrian behavior in real time. His complementary research on social navigation couples motion prediction with planning, effectively addressing the long-standing challenge of robots moving naturally among people. With both papers already garnering 7 citations shortly after publication, Mahjoub’s work is rapidly shaping the future of autonomous systems in human-centric spaces. His innovative fusion of social Long Short-Term Memory (LSTM) models with robust control architectures marks a significant step toward practical, real-world deployment of service and collaborative robots.
Research Focus
Key Achievements
Top Papers
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- 2