A. K. M. Nadimul Haque

University of Dhaka, Australian Centre for Robotic Vision

Papers

Total Citations

H-Index

About

A. K. M. Nadimul Haque is a researcher at the intersection of artificial intelligence, healthcare robotics, and human-robot interaction. His work focuses on developing intelligent systems that can learn and adapt in real-world environments, with a particular emphasis on rehabilitation and assistive technologies. Haque’s most cited paper, “AI-Driven Stroke Rehabilitation Systems and Assessment: A Systematic Review” (2022, 75 citations), critically evaluates how AI can address the shortage of skilled therapists by automating patient monitoring and therapy assessment, making rehabilitation more accessible and cost-effective. He also contributed to “Constrained Bootstrapped Learning for Few-Shot Robot Skill Adaptation” (2024), which introduces a novel hybrid method combining learning from demonstration and reinforcement learning. This approach enables robots to quickly adapt to new tasks online by seeding learning with a compact skill model, improving efficiency and stability in dynamic settings. Haque’s work has significant implications for personalized healthcare and autonomous robotics, bridging the gap between theoretical AI and practical deployment. His research continues to push the boundaries of how machines learn from limited data, aiming to create more responsive and capable robotic systems for real-world applications.