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About

Hoorieh Mazdarani is a researcher whose work spans intelligent control systems and medical robotics, with a particular focus on ultrasound-guided surgical assistance and adaptive robot control. Her early contributions include the development of an adaptive Nonlinear Model Predictive Controller (NMPC) for robot manipulators, addressing real-world challenges such as parameter uncertainties, unknown nonlinearities, and payload variations — a technically demanding problem in autonomous robotics. More recently, her research has shifted toward robot-assisted percutaneous nephrolithotomy (PCNL), a minimally invasive procedure for kidney stone removal, where she has made notable strides in ultrasound-guided needle tracking using visual servoing techniques. Her work integrates confidence maps and both in-plane and out-of-plane tracking strategies to improve surgical precision and reduce the dexterity burden on surgeons. Collectively, her publications have accumulated citations across a growing body of work, reflecting increasing recognition in the surgical robotics community. Mazdarani's research sits at a compelling intersection of control theory, medical imaging, and clinical application, making her contributions particularly relevant for students and researchers interested in autonomous surgical systems and intelligent robotic control.