Mohammad Biglarbegian

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Capabilities
Design, modeling, control and optimization of versatile robotic systems and in general mechatronic systems, developing advanced control, estimation, optimization algorithms for autonomous systems, developing intelligent control systems for vehicles and robotic systems, developing advanced algorithms using machine learning/artificial intelligence for automated systems specially in manufacturing and agriculture.
Education and Employment Background
Dr. Mohammad Biglarbegian obtained his PhD from the Mechanical & Mechatronics Engineering from the University of Waterloo, M.A.Sc., and B.A.Sc. from the universities of Toronto and Tehran, respectively. He joined the Mechanical Engineering group in the University of Guelph School of Engineering in 2011 and is the founder and director of the Autonomous and Intelligent Control for Vehicles lab at the University of Guelph.
Research Themes
Biglarbegian’s research is focused on modeling, control, and optimization of mechatronics systems specially for various robotic and vehicular systems. His research explores topics surrounding autonomous vehicles (i.e. mobile robots and driverless cars) using artificial intelligence and machine learning. Key areas of focus include:
- Autonomous systems. Today, autonomous systems are used in many different applications, ranging from mobile robots used as vacuum cleaners to driverless cars. However, there are challenges related to navigating such robots in dynamic and uncertain environments. The thrust of my research is to develop novel algorithms for these complex systems using advanced techniques including artificial intelligence and machine learning.
- Robotics. modeling, control, optimization of many robotic platforms such as mobile manipulators, soft robots, humanoid robots, etc. is of interest. One particular area is
- Control & Intelligent systems. Variety of advanced control techniques such as intelligent control, data-driven control, etc. is of particular interest for complex mechatronics systems in developing smart systems.
- Automotive; autonomous vehicles. Developing algorithms for autonomous vehicles is essential for safe operation of such. This research involves developing algorithms to help these vehicles stay collision-free while satisfying other constraints such as minimizing fuel consumption.
- Applications of Machine Learning and Artificial Intelligence (AI): Applications of various machine learning and artificial intelligence techniques for versatile applications and systems are of also interest.
Highlights
- Research Excellence Award, University of Guelph, 2018
- Associate Editor of the International Journal of Robotics and Automation, 2016-present
- Senior Member of the Institute of Electrical and Electronics Engineers (IEEE), 2014-present
Media Coverage
- CEPS Research Highlight: Working Together
- University of Guelph News: Green Technology Offers Solutions for Developing Countries