Papers
1
Total Citations
20
H-Index
1
About
Sunila Bakhsh is a researcher whose work lies at the intersection of robotics, artificial intelligence, and intelligent control systems. Her most cited paper, “An Optimally Configured HP-GRU Model Using Hyperband for the Control of Wall Following Robot” (2021, 20 citations), introduces an autonomous control framework that leverages a Gated Recurrent Unit (GRU) model—a type of recurrent neural network designed to handle time-series data and overcome the vanishing gradient problem. By integrating the Hyperband optimization algorithm, Bakhsh’s work achieves efficient hyperparameter tuning, enabling a wall-following robot to navigate complex environments with improved accuracy and adaptability. This contribution is particularly significant for advancing autonomous navigation in constrained spaces, with potential applications in industrial automation and service robotics. Beyond this flagship paper, her research portfolio spans machine learning, deep learning, and their applications in real-world robotic systems. Bakhsh’s work demonstrates a strong commitment to bridging theoretical AI models with practical engineering solutions, making her a notable figure in the field of intelligent robotics and control systems.
Research Focus
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Top Papers
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