Mr. Ibrahim Khalil Kabir | Engineering and Technology | Best Researcher Award
King Fahd University of Petroleum and Minerals | Saudi Arabia
Ibrahim Khalil Kabir is a control and robotics researcher working at the intersection of control theory and artificial intelligence, with a strong focus on learning-based robotics, socially aware navigation, and human–robot interaction. He holds an MSc in Systems and Control Engineering and a BEng in Mechatronics Engineering, with a solid academic record and advanced training in autonomous systems. His research experience spans graduate teaching and research assistantships, where he contributed to robot path planning, navigation, and hands-on laboratory instruction using real robotic platforms. His scholarly output includes peer-reviewed journal and conference publications covering UAV control, mobile robot navigation, deep reinforcement learning, and socially aware robotic systems. According to Google Scholar, his research profile reflects an emerging h-index supported by multiple indexed documents and a steadily growing citation count, indicating increasing impact in robotics and intelligent control research. His work has appeared in reputable venues such as IEEE Access, Machine Learning and Knowledge Extraction, and IEEE conferences. He has received several academic honors, including national merit scholarships and highest GPA awards. Overall, his research trajectory demonstrates a strong foundation and growing influence in intelligent robotics, positioning him well for advanced doctoral research in learning-enabled autonomous systems.
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Featured Publications
Optimal Gain Scheduling for Fault-Tolerant Control of Quadrotor UAV Using Genetic Algorithm-Based Neural Network
Trajectory Tracking of Unmanned Aerial Vehicles using Backstepping Approach-based Sliding Mode Control
Autonomous Mobile Robot Path Planning Techniques—A Review: Classical and Heuristic Techniques
Learning to Navigate in Mixed Human–Robot Crowds via an Attention-Driven Deep Reinforcement Learning Framework