A. Khalid

Papers

Total Citations

H-Index

About

A. Khalid is a pioneering researcher at the intersection of robotics, neuromorphic computing, and artificial intelligence, whose work is shaping the future of autonomous navigation. Khalid’s primary contributions lie in developing bio-inspired algorithms that enhance the robustness and efficiency of mobile robot path planning. Their landmark paper, "DSQN: Robust path planning of mobile robot based on deep spiking Q-network" (2025), has already garnered 23 citations, signaling a significant impact in the field. This work introduces a novel deep spiking Q-network that leverages spiking neural networks—a brain-inspired computing paradigm—to achieve energy-efficient and resilient decision-making in dynamic environments. By integrating reinforcement learning with spiking dynamics, Khalid addresses critical challenges in real-time obstacle avoidance and adaptive path optimization, outperforming traditional deep reinforcement learning approaches. This research not only advances theoretical understanding but also offers practical solutions for autonomous systems operating under resource constraints. Khalid’s work is widely recognized for bridging the gap between biological plausibility and engineering application, making them a key figure in the next generation of intelligent robotics.