Shadi Banitaan

Papers

Total Citations

H-Index

About

Shadi Banitaan’s research lies at the intersection of autonomous robotics and social media security, with a focus on intelligent path planning and machine learning-based bot detection. In robotics, Banitaan has advanced the efficiency of autonomous navigation by developing a partitioning-based approach for robot path planning, which strategically divides the environment to accelerate collision-free route computation. Complementing this, their work on coarse grid partitioning to speed up A* robot navigation further optimizes real-time decision-making for autonomous agents, addressing a core challenge in the field. On the cybersecurity side, Banitaan applies machine learning techniques to distinguish human users from automated bot accounts on Twitter, tackling the growing threat of social media manipulation. This dual-threat research—spanning physical robot autonomy and digital identity verification—demonstrates a versatile approach to solving complex, real-world problems. With key papers accumulating citations that reflect their emerging impact, Banitaan’s contributions are particularly valuable for students and researchers interested in practical AI applications, from efficient robotic movement to safeguarding online discourse against exploitation.