Arash is an Associate Professor with the Department of Mechanical and Mechatronics Engineering  and cross-appointed at the Systems Design Engineering department at the University of Waterloo. 

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He is the head of Neuromechanics and Assistive Robotics Laboratory, and a core member of Biomedical Engineering graduate program. Arash is a member of UW Robohub, Centre of Bioengineering and Biotechnology (CBB) and Waterloo AI, at the University of Waterloo. 

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He is also an affiliated scientist at the KITE institute, Toronto Rehabilitation Institute, University Health Network.

 

Arash has served as chair of NSERC selection committee from 2021-2023 and has been a member of selection committee since 2020. 

He is also a core member of Mechatronics, Robotics and Control Technical Committee of the Canadian Society of Mechanical Engineering.  

He is an Associate Editor for the IEEE Transactions on Neural Systems and Rehabilitation Engineering. 

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Before, he was a Research Associate in Human Robotics Group at the Imperial College London, from August 2015 to December 2017. He was also a Postdoctoral Researcher at Ecole Polytechnique Fédéral de Lausanne (EPFL) from March 2014 to August 2015 in the Laboratory of Movement Analysis and Measurement. He obtained his PhD from EPFL in February 2014. 

    

His main research interests are:

1) to investigate human neuromechanics (neural control of movements and biomechanics), motor control and learning using system identification and machine learning techniques

2) to investigate human-robot interaction, collaborative control, co-adaptation, and optimal policy for personalized assistance and rehabilitative robotic systems 

3) to develop intelligent and learning-based robotics systems for assistance and sensorimotor augmentation 

4) to develop intelligent wearable systems to monitor and feedback human subject states using a variety of light weight sensors and machine learning techniques

5) to develop AI-based modeling and optimization of complex processes, with applications in manufacturing, robotics, biomedical engineering and well being

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The subject-specific neuromechanical models, control theory and machine learning techniques enable us to build personalized adaptive controller to provide assistance/rehabilitation through robotic systems such as wearable exoskeletons. Affected movement and locomotion due to neurological conditions, aging, orthopedic disease or amputation are also investigated in his research group. 

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Teaching activities:

at UWaterloo:

ME   780 (Human Movement Neuromechanics)

ME   547 (Robot Manipulators: Kinematics, Dynamics, and Control )

MTE 546 (Multi-sensor Data Fusion )

MTE 360 (Automatic Control Systems)

ME   360 (Introduction to Control Systems)

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at Imperial College:

Human Neuromechanical Control and Learning

Machine Learning and Neural Computations

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at EPFL:

Analysis and Modelling of Locomotion

Sensors in Biomedical Instrumentation

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at U of Tehran:

Pattern Recognition

Machine Learning