Shayan Khorsandi
Papers
1
Total Citations
3
H-Index
1
About
Shayan Khorsandi is a researcher in robotics and artificial intelligence, with a particular focus on humanoid robot motion planning and predictive modeling. His most cited work, "Ball Path Prediction for Humanoid Robots: Combination of k-NN Regression and Autoregression Methods" (2022), introduces a novel hybrid approach that integrates k-nearest neighbor regression with autoregressive techniques to enhance a robot’s ability to anticipate and react to dynamic objects in real time. This contribution addresses a critical challenge in humanoid robotics—enabling machines to perform complex, reactive tasks in unstructured environments. Though early in his career, Khorsandi’s work has already garnered attention with several citations, signaling its relevance to advancing autonomous decision-making. His research bridges machine learning and control systems, offering practical solutions for improving robot agility and perception. As the field moves toward more adaptive humanoid systems, Khorsandi’s methods provide a foundation for future innovations in real-time object tracking and interaction.
Research Focus
Key Achievements
Top Papers
- 1