Papers
32
Total Citations
816
H-Index
16
About
Mahdi Khoramshahi is a robotics and human-robot interaction researcher whose work spans adaptive control, dynamical systems, biomechanics, and clinical applications of robotics. He is perhaps best known for pioneering dynamical system approaches to complex robotic challenges, including task-adaptation in physical human-robot interaction (112 citations) and the remarkable feat of programming robots to softly catch fast-flying objects in real time (100 citations). His research elegantly bridges theoretical rigor with experimental validation, extending dynamical system frameworks to contact tasks involving precise force control and adaptation — critical capabilities for robots operating in unstructured environments. Khoramshahi has also made significant contributions to quadruped locomotion, demonstrating that active spine control dramatically improves speed and stability in bounding robots (95 citations), with complementary work exploring energy-efficient piecewise linear spine designs. Equally notable is his interdisciplinary reach into clinical neuroscience: he has explored humanoid robots as diagnostic and therapeutic tools in schizophrenia research, investigating socio-motor biomarkers and the influence of robot-delivered facial feedback on social cognition. With over 575 cumulative citations, his portfolio reflects both technical depth and a commitment to deploying robotics meaningfully at the intersection of engineering, medicine, and human welfare.
Research Focus
Key Achievements
Top Papers
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- 4A Dynamical System Approach to Motion and Force Generation in Contact Tasks48 citations · 2019
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- 6Unravelling socio-motor biomarkers in schizophrenia42 citations · 2017
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- 9Force Adaptation in Contact Tasks with Dynamical Systems30 citations · 2020
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