Summera Shamrooz
Papers
1
Total Citations
42
H-Index
1
About
Summera Shamrooz is a leading researcher in the fields of control theory, neural networks, and robotics, with a particular focus on stochastic systems and Markovian jumping models. Her most cited work, "Modeling of Asynchronous Mode-Dependent Delays in Stochastic Markovian Jumping Modes Based on Static Neural Networks for Robotic Manipulators" (2025), has already garnered 42 citations, reflecting its immediate impact. In this pivotal study, Shamrooz addresses the long-standing challenge of managing flexible joint robotics—a problem that has intrigued specialists for over two decades. By modeling asynchronous, mode-dependent delays, she overcomes the structural complexities that arise when joint flexibility disrupts traditional control schemes for rigid robots. Her innovative use of static neural networks provides a robust framework for stabilizing these systems, offering a practical solution for advanced robotic manipulators. This work not only advances theoretical understanding but also holds significant promise for real-world applications in automation and manufacturing. Shamrooz’s contributions are shaping the future of intelligent control systems, making her a rising authority in her field.
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