Avinash Rohra

University of Science and Technology of China

Papers

Total Citations

172

H-Index

About

Avinash Rohra is a researcher at the forefront of intelligent control systems and bio-inspired robotics, with a focus on enhancing the autonomy and robustness of robotic manipulators and mobile platforms. His most-cited work, a practical study of active disturbance rejection control for rotary flexible joint robot manipulators, garnered 149 citations, demonstrating significant interest in his approach to mitigating real-world dynamic uncertainties in flexible systems. More recently, Rohra has pioneered the integration of spiking neural networks with reinforcement learning, introducing the Deep Spiking Q-Network (DSQN) for robust mobile robot path planning. This 2025 contribution, already accruing 23 citations, marks a notable step toward energy-efficient, event-driven navigation algorithms that mimic biological neural processing. While one of his earlier papers was retracted, his subsequent work on DSQN highlights his resilience and commitment to advancing neuromorphic control. Rohra’s research bridges the gap between classical disturbance rejection and cutting-edge neural computation, offering practical solutions for next-generation autonomous systems.