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Hashim A. Hashim Mohamed, Ph.D., P.Eng., SMIEEE

Assistant professor

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

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Dr. Hashim Mohamed is currently (Jan.2022-Present) an Assistant Professor at the Department of Mechanical and Aerospace Engineering at Carleton University, Ottawa, Ontario, Canada. Between Aug.2019 and Dec.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 July 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 Ontario, Canada, and a senior member of IEEE.

Academic Degrees

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 related to: Perception and Navigation, Control, and Trajectory Planning. 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), autonomous underwater vehicles (AUVs), mobile robots, satellites, and other robotics applications. My research interests include but are not limited to

  • Guidance, Perception & Navigation, and Control.
  • Vision-aided inertial navigation systems for UAVs/drones and ground/mobile robots ,
  • 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

 

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