Mahdi Hejrati

Tampere University, Sharif University of Technology

Papers

5

Total Citations

41

H-Index

5

About

Mahdi Hejrati is an emerging robotics and control systems researcher whose work centers on advanced control methodologies for human-robot interaction, exoskeleton systems, and rehabilitation robotics. His research addresses some of the most pressing challenges in safe and adaptive physical human-robot interaction (pHRI), particularly in the context of upper limb exoskeletons designed to assist and rehabilitate human operators. Hejrati's most impactful contributions include the development of nonlinear subsystem-based adaptive impedance control frameworks and decentralized neuroadaptive control schemes, which enhance both stability and safety in complex, contact-rich robotic tasks. His work on virtual decomposition control for 7-DoF redundant exoskeletons introduced a natural adaptation law that reduces the need for manual parameter tuning — a notable practical advancement. Beyond exoskeletons, he has explored virtual reality-integrated rehabilitation robots for children with cerebral palsy, demonstrating a commitment to socially meaningful applications. More recently, his orchestrated robust controller for heavy-duty hydraulic manipulators signals a broadening scope toward industrial automation. With publications accumulating citations across multiple venues since 2019, Hejrati represents a productive voice bridging theoretical control design with real-world rehabilitation and industrial robotics challenges.

Research Focus

Key Achievements

5
H-Index
5
Papers
41
Total Citations
8
Avg Citations/Paper
🏆 Most Cited Paper
Nonlinear Subsystem-Based Adaptive Impedance Control of Physical Human-Robot-Environment Interaction in Contact-Rich Tasks
11 citations · 2023
📈 Most Prolific Year: 2023 (2 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: Tampere University, Sharif University of Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago