Seyed-Farzad Mohammadi

Papers

Total Citations

H-Index

About

Seyed-Farzad Mohammadi is a researcher specializing in haptic systems, medical robotics, and dynamic control, with a focus on advancing surgical training technologies. His major contributions center on the development and calibration of ARASH:ASiST, a 3-DOF haptic device designed for intraocular surgery training. In his most-cited work, "On The Dynamic Calibration and Trajectory Control of ARASH:ASiST" (2022), he derived a linear regression form of the system’s dynamic formulation to enable precise parameter calibration and trajectory control, enhancing the fidelity of surgical simulations. This foundational research has garnered 3 citations, reflecting its niche but critical impact in the field of haptic-assisted medical training. Mohammadi’s work bridges robotics and ophthalmology, offering a platform that improves surgeon dexterity and patient safety through realistic haptic feedback. His achievements include advancing the practical application of dynamic modeling in medical devices, positioning him as a contributor to the next generation of surgical training tools. For students and researchers, his research exemplifies the integration of control theory and biomechanics to solve real-world clinical challenges.