Niloy Sikder
Papers
2
Total Citations
61
H-Index
2
About
Niloy Sikder is a researcher at the forefront of intelligent robotics and biomedical signal processing. His work bridges the gap between autonomous machine learning and human-machine interaction, with a primary focus on reinforcement learning (RL) for robotic control and the analysis of surface electromyography (sEMG) signals for prosthetic development. In his highly cited systematic review (46 citations), Sikder provided a comprehensive roadmap of RL applications in robotics over the past decade, highlighting how this paradigm is revolutionizing autonomous decision-making in the fourth industrial revolution. His impactful work on finger movement classification (15 citations) demonstrates a deep commitment to advancing prosthetics, where he extracted statistical and frequency features from sEMG signals to enable more natural, intuitive control of robotic limbs. By tackling both the algorithmic foundations of robot learning and the practical challenges of biosignal interpretation, Sikder is contributing to a future where machines not only learn from their environment but also respond seamlessly to human intent. His research is essential reading for anyone interested in the convergence of AI, robotics, and assistive technology.
Research Focus
Key Achievements
Top Papers
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