PhD Candidate

Email: a.nasr@uwaterloo.ca

Biography

Ali Nasr is a Ph.D. Candidate in Control, Robotics, and Biomechatronics Systems Design Engineering at the University of Waterloo, a Graduate Research Assistant with Prof. John McPhee, and a Graduate Teaching Assistant at the Department of Systems Design Engineering. Ali specializes in robotic engineering, with an emphasis on modeling, control, optimization, and automation of robotic and mechatronic systems.
His doctoral research focuses on I. modeling and simulation of upper-limb biomechatronic (human-exoskeleton) systems with active and passive actuation, II. modeling muscle biomechanics using artificial intelligence/machine learning for autonomous exoskeleton control during object manipulation and rehabilitation, III. model predictive controlling of an active exoskeleton robot using stochastic myoelectric biosignal, and IV. part design, manufacturing, and controlling the first prototype of the shoulder exoskeleton robot.

Education

• PhD Candidate in Systems Design Engineering, University of Waterloo (Canada)
• MSc in Mechatronics Engineering, K.N. Toosi University of Technology (Iran)
• BSc in Mechanical Engineering, Isfahan University of Technology (Iran)

Publication

[24] Nasr A, and McPhee J. (2022). Performance of assist-as-needed control based on EMG-driven MuscleNET for a shoulder exoskeleton robot, Under preparation.
[23] Febrer-Nafria M, Nasr A, Ezati M, Brown P, Font-Llagunes J M, McPhee J. (2022). Predictive dynamic simulation of musculoskeletal systems: A review. Under preparation.
[22] Nasr A, and McPhee J. (2022). Multibody constrained dynamic modelling of human-exoskeleton: Toward optimal design and control of active-passive wearable robots. Submitted to The 6th Joint International Conference on Multibody System Dynamics and The 10th Asian Conference on Multibody Dynamics.
[21] Nasr A, Bell S, and McPhee J. (2022). Optimal design of active-passive shoulder exoskeletons: A computational modeling of human-robot interaction. Ready for submission.
[20] Nasr A, Hashemi A, and McPhee J. (2022). Scalable Musculoskeletal (BodySim) Model for Dynamic Simulations of Movement: I. Upper body. Ready for submission.
[19] Nasr A and McPhee J. (2022). Biarticular MuscleNET: A machine learning model of biarticular muscles. In Proceedings of the North American Congress of Biomechanics (NACOB).
[18] Nasr A, Hashemi A, and McPhee J. (2022). Model-based mid-level regulation for assist-as-needed hierarchical control of wearable robots: A preliminary study of human-robot adaptation. Robotics 11 (1) 20. DOI: 10.3390/robotics11010020
[17] Nasr A, Ferguson S, and McPhee J. (2022). Model-based design and optimization of passive shoulder exoskeletons. ASME. Journal of Computational and Nonlinear Dynamics. DOI: 10.1115/1.4053405
[16] Nasr A, Inkol K A, Bell S, and McPhee J. (2021). InverseMuscleNET: Alternative machine learning solution to static optimization and inverse muscle model. Frontiers in Computational Neuroscience. DOI: 10.3389/fncom.2021.759489
[15] Nasr A, Bell S, He J, Whittaker R L, Jiang N, Dickerson C R, and McPhee J. (2021). MuscleNET: Mapping electromyography to kinematic and dynamic biomechanical variables. Journal of Neural Engineering. vol. 18, no. 4, p.0460d3. DOI: 10.1101/2021.07.07.451532.
[14] Nasr A, Ferguson S, and McPhee J. (2021). Model-based design and optimization of passive shoulder exoskeletons. In Proceedings of the ASME 2021 Virtual International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (IDETC-CIE), vol. 85468, p. V009T09A029. DOI: 10.1115/DETC2021-69437
[13] Nasr A, Laschowski B, and McPhee J. (2021). Myoelectric control of robotic leg prostheses and exoskeletons: A review. In Proceedings of the ASME 2021 Virtual International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (IDETC-CIE), vol. 85444, p. V08AT08A043. DOI: 10.1115/DETC2021-69203
[12] Nasr A, He J, Jiang N, and McPhee J. (2021). Muscle modelling using machine learning and optimal filtering of sEMG signals. In Proceedings of the 45th American Society of Biomechanics (ASB) Annual Conference, pp. 85.
[11] Nasr A, He J, Jiang N, and McPhee J. (2020). Activation torque estimation of muscles by forward neural networks (Forward-MuscleNET) for sEMG-based control of assistive robots. In Proceedings of the 7th International Conference of Control, Dynamic Systems, and Robotics (CDSR’20). DOI: 10.11159/cdsr20.146.
[10] Nasr A, and McPhee J. (2020). Control-oriented muscle torque (COMT) model for EMG-based control of assistive robots. In Proceedings of the 7th International Conference of Control, Dynamic Systems, and Robotics (CDSR’20). DOI: 10.11159/cdsr20.144.
[9] Nasr A, Arami A, and McPhee J. (2019). Optimal cost function for predicting upper-limb movement with external load. In Proceedings of the 16th annual Ontario Biomechanics Conference (OBC2019).
[8] Ghanbari M, Mousavi M, Moosavian SAA, Nasr A, and Zarafshan P. (2017). Experimental analysis of an optimal redundancy resolution scheme in a cable-driven parallel robot. In Proceedings of the IEEE 5th RSI International Conference on Robotics and Mechatronics (ICRoM2017), pp. 33-38. DOI: 10.1109/ICRoM.2017.8466229.
[7] Mousavi M, Ghanbari M, Nasr A, Moosavian SAA, and Zarafshan P. (2016). Sensory feedback performance improvement on Robocab: An experimental approach to wire-driven parallel manipulator. In Proceedings of the IEEE 4th International Conference on Robotics and Mechatronics (ICRoM2016), pp. 477-482. DOI: 10.1109/ICRoM.2016.7886787.
[6] Nabipour M, Arteghzadeh N, Moosavian SAA, and Nasr A. (2016). Visual servoing in a cable robot using microsoft kinect V2 sensor. In Proceedings of the IEEE 4th International Conference on Robotics and Mechatronics (ICRoM2016), pp. 560-565. DOI: 10.1109/ICRoM.2016.7886803.
[5] Nasr A, and Moosavian SAA. (2016). Multi-objective optimization design of spatial cable-driven parallel robot equipped with a serial manipulator. Modares Mechanical Engineering 16, no. 1, pp. 29-40.
[4] Nasr A, and Moosavian SAA. (2015). Multi-criteria design of 6-DoF fully-constrained cable driven redundant parallel manipulator. In Proceedings of the IEEE 3rd RSI International Conference on Robotics and Mechatronics (ICRoM2015), pp. 001-006. DOI: 10.1109/ICRoM.2015.7367591.
[3] Sajadi MR, Nasr A, Moosavian SAA, and Zohoor H. (2015). Mechanical design, fabrication, kinematics and dynamics modeling, multiple impedance control of a wrist rehabilitation robot. In Proceedings of the IEEE 3rd RSI International Conference on Robotics and Mechatronics (ICRoM2015), pp. 290-295. DOI: 10.1109/ICRoM.2015.7367799.
[2] Parandian Y, Arabshahi HZ, Nasr A, and Moosavian SAA. (2015). Time optimized digital image processing of ball and plate system using artificial neural network. In Proceedings of the IEEE 3rd RSI International Conference on Robotics and Mechatronics (ICRoM2015), pp. 146-151. DOI: 10.1109/ICRoM.2015.7367775.
[1] Nasr A, Asadi F, Azami K, and Ziaei-Rad S. (2015). An optimization of trunk angle in biped robots in generating a stable path in up-stair walking. In Proceedings of the 23rd International Mechanical Engineering Conference (ISME2015).

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Affiliation: 
University of Waterloo