Mohamad Shahab
Assistant Professor Faculty of Engineering and Architectural Science Department of Electrical, Computer, and Biomedical Engineering Toronto, Ontario mshahab@torontomu.ca
Expert In
Bio/Research
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 ha...
Click to Expand >>
Click to Expand >>
Bio/Research
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’s 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 Toronto Metropolitan University, Shahab helps his students master these fundamentals and apply them to wide-ranging applications that can benefit the world – from smart city technologies to energy-efficient transportation.
Click to Shrink <<
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’s 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 Toronto Metropolitan University, Shahab helps his students master these fundamentals and apply them to wide-ranging applications that can benefit the world – from smart city technologies to energy-efficient transportation.
Click to Shrink <<