Mahrukh Shahid
Papers
1
Total Citations
5
H-Index
1
About
Mahrukh Shahid is a rising researcher in the field of robotics and artificial intelligence, with a primary focus on autonomous navigation and deep reinforcement learning. Her most notable contribution is the development of dynamic goal-tracking algorithms for differential drive robots, a critical challenge in real-world robotic mobility. In her highly regarded 2023 paper, "Dynamic Goal Tracking for Differential Drive Robot Using Deep Reinforcement Learning," Shahid introduced a novel framework that enables robots to adaptively pursue moving targets in unstructured environments, achieving robust performance without explicit path planning. This work, already garnering 5 citations, demonstrates her ability to bridge theoretical reinforcement learning with practical robotic control. Shahid’s research addresses key limitations in traditional navigation systems, offering scalable solutions for applications ranging from warehouse automation to search-and-rescue operations. By integrating deep learning with classical robotics, she is helping to define the next generation of intelligent, responsive machines. Her early impact signals a promising trajectory in advancing autonomous systems that can learn and react in real time.
Research Focus
Key Achievements
Top Papers
- 1