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Abolfazl Mohebbi
B.Sc. (IUT), M.A.Sc. (Concordia), Ph.D. (Poly), Postdoc (McGill/Poly), Postdoc (Harvard)

Research interests and affiliations

Research interests

Professor Mohebbi's research interests are related to the development of new methods and devices for assistive, rehabilitation and medical technologies. Consequently, he has integrated 4 research axes in his group and for each axis, the following research interests are considered:

1- Neuromuscular Control and Rehabilitation:

  • Vision contributions to human upright stance
  • Interactions between vision and proprioceptive sensory systems in human upright stance
  • Virtual Reality for balance rehabilitation in P-VL patients
  • Deep-learning approaches for identification of human balance mechanism in upright stance

2- Biomechatronics:

  • Wearable devices and sensors
  • Intelligent Health Monitoring
  • Control of Artificial Organs
  • Mechatronic Prosthetics, Orthosis and Exoskeletons

3- Medical and Assistive Robotics:

  • Path Planning and Control of Surgical Robotics
  • Design and control of Assistive Robotics
  • Visual Servoing

4- Applied Artificial Intelligence:

  • Biomedical System Identification using AI
  • Deep Neural Networks for Tumor Detection
  • Neuromuscular Diagnostics Using Convolutional Networks
Expertise type(s) (NSERC subjects)
  • 1701 Engineering design
  • 2509 Control systems
  • 2600 ROBOTICS
  • 2716 Virtual reality and related simulations
  • 2715 Optimization
  • 2603 Computer vision
  • 2604 Intelligent systems applications


Recent publications
Journal article
Amiri, P., Mohebbi, A. & Kearney, R. (2019). Experimental Methods to Study Human Postural Control. Journal of Visualized Experiments, (151). Retrieved from
Journal article
Mohebbi, A., Achiche, S. & Baron, L. (2019). Integrated and concurrent detailed design of a mechatronic quadrotor system using a fuzzy-based particle swarm optimization. Engineering Applications of Artificial Intelligence, 82, 192-206. Retrieved from
Conference paper
Mohebbi, A., Achiche, S. & Baron, L. (2018). Data-driven approaches in multi-criteria decision support for mechatronic systems design [Oral presentation]. Presented at the DSR Workshop on Data Driven Design and Learning, Montréal, Québec.
Journal article
Mohebbi, A., Achiche, S. & Baron, L. (2018). Multi-criteria fuzzy decision support for conceptual evaluation in design of mechatronic systems: a quadrotor design case study. Research in Engineering Design, 29(3), 329-349. Retrieved from


Abolfazl Mohebbi obtained his bachelor’s degree in Mechanical Engineering from Isfahan University of Technology (IUT), Iran, in 2009. He received a Master's degree from Concordia University (2013) and a Doctorate degree from Polytechnique Montreal (2017) both in in Mechanical Engineering with the specializations in robotics, control and mechatronics.

After holding industrial positions for almost three years, he returned to the academia as a postdoctoral researcher until 2020. As a postdoctoral fellow at Polytechnique, McGill and Harvard University, his research activities were focused on various fields of Biomedical Engineering, Neuromuscular Control, Assistive Technologies and Artificial Intelligence (AI).

Abolfazl Mohebbi is now an Assistant Professor in the Mechanical Engineering Department at Polytechnique Montréal. He also holds the Chair in Assistive and Rehabilitation Technologies, co-founded by the TransMedTech Institute (iTMT) of Polytechnique Montréal, the CHU Sainte-Justine research center and the Technopole in Pediatric Rehabilitation.