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About

Sehraneh Ghaemi is a leading researcher in intelligent control systems and robotics, specializing in fuzzy logic, neural networks, and predictive control for complex, uncertain environments. Her major contributions lie in developing advanced type-2 fuzzy neural network controllers that address the challenges of nonlinear systems with input delays—a critical issue in real-world automation. Notably, her work on “Indirect predictive type-2 fuzzy neural network controller for a class of nonlinear input-delay systems” (2017) has garnered 15 citations, showcasing its impact on robust control theory. Ghaemi has also made significant strides in robotic path planning, proposing innovative fuzzy methods for dynamic environments with unknown moving obstacles. Her 2014 paper on “A fuzzy multi-stage path-planning method for a robot in a dynamic environment” (14 citations) introduced practical, real-time navigation strategies that overcome limitations of prior approaches. Additionally, her 2019 study on feedback error learning-based predictive control (9 citations) further advanced the field by integrating prediction and learning for uncertain systems. With a career focused on bridging theoretical fuzzy systems and applied robotics, Ghaemi’s work continues to influence autonomous navigation and adaptive control, offering robust solutions for real-time decision-making in unpredictable settings.