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Dr. Mohamad T. Shahab

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Assistant Professor
DepartmentElectrical, Computer and Biomedical Engineering
Areas of ExpertiseControl Theory, Robotics, Adaptive Control, Autonomy, Control & Optimization, Autonomous Systems

Assistant Professor
BSc, MSc, PhD

"I seek to bridge control theory and learning to answer the world鈥檚 autonomy questions."

A subject matter expert in robotics, adaptive control, and optimization, Mohamad Shahab helps to evolve autonomous systems to benefit people and communities. As an undergraduate, Shahab was always fascinated by the concept of autonomous robots. Building on this passion, over the last decade he has led various engineering systems research projects for academia and industry. 

How does a self-driving car respond safely to changing weather conditions? How do you teach drones to work together in flight? For Shahab, working at the intersection of control theory and machine learning is the key to uncovering solutions for society鈥檚 autonomy challenges. Using engineering tools based on control theory, he evaluates adaptive and learning-based systems to account for risk. Shahab is a proponent that the greater the risk, the greater the need to understand the fundamentals of behaviour. As a professor at 91福利, Shahab helps his students master these fundamentals and apply them to wide-ranging applications that can benefit the world 鈥 from smart city technologies to energy-efficient transportation. 

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飦 ENG-451
飩 416-979-5000 ext. 556686
 mshahab@torontomu.ca

飩&苍产蝉辫;

飩&苍产蝉辫;

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Subject matter expert in adaptive control and learning-based systems. 

Shahab has over ten years of experience in control systems engineering research. Before joining 91福利, Shahab held research positions at the King Abdullah University of Science and Technology鈥檚 Robotics, Intelligent Systems, and Control (RISC) Lab, as well as at the University of Waterloo and KFUPM. 

 

Specializations
 
  • Control Theory
  • Robotics
  • Adaptive Control
  • Autonomy
  • Control & Optimization
  • Autonomous Systems

Additional Info

View Mohamad Shahab's

Shahab, M.T., Miller, D.E., 鈥淩evisiting Model Reference Adaptive Control: Linear-like Closed-loop Behavior,鈥 IEEE Transactions on Automatic Control, 2024.

Shahab, M.T., Miller, D.E., 鈥淚nherent Robustness in the Adaptive Control of a Large Class of Systems,鈥 International Journal of Adaptive Control and Signal Processing, vol. 38, no. 7, pp. 2423-2442, 2024.

Wali, O., Shahab, M.T., Feron, E., 鈥淎 Non-planar Assembly of Modular Tetrahedral-shaped Aerial Robots,鈥 in 2023 IEEE International Conference on Robotics and Automation (ICRA), 2023, pp. 11901-11907.

Shahab, M.T., Wali, O., Feron, E., 鈥淎utomatic Identification of a Modular Unmanned Aerial System (UAS) with Experimental Verification,鈥 AIAA 2023-2160. AIAA SciTech 2023 Forum. 2023.

Shahab, M.T., Garanger, K., Feron, E., 鈥淐ontrol of an assembly of aerial vehicles under uncertainty,鈥 in 2022 American Control Conference (ACC), 2022, pp. 514-519.

Shahab, M.T., Miller, D.E., 鈥淎symptotic tracking and linear-like behavior using multi-model adaptive control,鈥 IEEE Transactions on Automatic Control, vol. 67, no. 1, pp. 203鈥219, 2022.

Shahab, M.T., Miller, D.E., 鈥淎daptive control of a class of discrete-time nonlinear systems yielding linear-like behavior,鈥 Automatica, vol.130, p.109691, 2021.

 

Education

Year

University

Degree

2020

University of Waterloo

PhD

2015

KFUPM

MSc

2007

KFUPM

BSc

Selected Courses