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Faculty and Staff / Hashim Mohamed

Hashim Mohamed

Assistant Professor

    Email:Hashim.Mohamed@carleton.ca
    Phone:613-520-2600, ext. 1224
    Building:Mackenzie, Room 3244
    Department:Mechanical and Aerospace Engineering
    Degrees:Degrees: B.Sc. (Mechatronics), M.Sc. (Systems & Control), and Ph.D. (Robotics & Control)
    Website:https://carleton.ca/hhashim/

    About

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    Hashim Mohamed is currently an Assistant Professor at the Department of Mechanical and Aerospace Engineering at Carleton University, Ottawa, Ontario, Canada. Between August of 2019 and December of 2021 he was an Assistant Professor at the Department of Engineering & Applied Science at Thompson Rivers University (TRU), Kamloops, British Columbia, Canada. He received the Ph.D. degree in robotics and control from the Department of Electrical and Computer EngineeringWestern University (UWO), London, Ontario, Canada, in 2019.

    Prior to this he received the M.Sc. degree in Systems and Control Engineering from the Department of Systems EngineeringKing Fahd University of Petroleum and Minerals (KFUPM), Dhahran, Saudi Arabia, and the B.Sc. degree in mechatronics from the Department of Mechanical EngineeringHelwan University (HU), Helwan, Egypt. He is a registered Professional Engineer (P.Eng.) in the province of British Columbia, Canada, and a senior member of IEEE.

    Education

    Teaching

    • MECH 5804 – Applied Artificial Intelligence (Graduate level)
    • MECH 5906 Directed Study – Vision-based Perception Robotics (Graduate level)
    • AERO 4504 – Avionics Systems
    • MAAE 3500 – Feedback Control Systems

    Research Interests

    The ultimate goal of my research is to develop novel technologies. I aspire to discover new ways to improve the performance of dynamical systems, in particular smart systems which include semi-automated and fully autonomous systems, such as unmanned aerial vehicles (UAVs/drones), unmanned underwater vehicles (UUVs), mobile robots, and other robotics applications. My research interests include but are not limited to

    • Guidance, navigation, and control,
    • Vision-aided inertial navigation systems,
    • Robot localization and mapping with inertial vision systems,
    • Filtering and estimation solutions: stochastic and deterministic,
    • Sensor fusion,
    • Distributed control of multi-agent systems,
    • Artificial intelligence, optimization techniques and metaheuristic algorithms (single and multi objective),
    • Deep learning tools

    The complete research profile can be found in GoogleScholar