Parham M. Kebria
Papers
20
Total Citations
740
H-Index
12
About
Parham M. Kebria is a robotics and artificial intelligence researcher whose work spans imitation learning, teleoperation systems, and autonomous robot control. His highly cited 2024 survey on imitation learning algorithms (172 citations) has established him as a leading voice in understanding how AI systems learn from human demonstration — a critical capability for autonomous driving, aerial robotics, and natural language applications. Equally influential is his foundational work on the kinematic and dynamic modelling of the UR5 manipulator (150 citations), which has become an essential reference for roboticists worldwide working with collaborative robotic arms. Kebria's contributions to teleoperation are particularly notable: his robust adaptive control scheme for handling time-varying delays and uncertainties (124 citations) and his adaptive Type-2 fuzzy neural-network controller (75 citations) together address some of the most persistent challenges in remotely operated robotic systems. His research further extends into rehabilitation robotics, autonomous navigation using evolutionary optimization, and deep imitation learning for autonomous driving. Across his body of work, Kebria demonstrates a consistent commitment to bridging theoretical control design with practical robotic implementation, making his research highly valuable to both academic and applied communities.
Research Focus
Key Achievements
Top Papers
- 1A Survey of Imitation Learning: Algorithms, Recent Developments, and Challenges172 citations · 2024
- 2Kinematic and dynamic modelling of UR5 manipulator150 citations · 2016
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