Mohsen Khadem

Reader in Robotics
Institute for Perception, Action and Behaviour
School of Informatics
University of Edinburgh
Address: Room 1.15, Bayes Centre,
10 47 Potterrow, Edinburgh EH8 9BT, U.K.
Tel: +44 (0) 131 650 2956
Lab Website


I'm a UKRI Future Leaders Fellow and Reader in Robotics, at School of Inofrmatics University of Edinburgh. I joined the School of Informatics in 2018. Previously I was a Post-Doctoral Researcher at the Wellcome/EPSRC Centre for Interventional and Surgical Sciences, University College London. I recieved my Ph.D. in Electrical and Computer Engineering from the University of Alberta, Canada in 2017, my M.Sc. in Biomechanics from the Sharif University of Technology, Iran, in 2013, and my B.Sc. in Mechanical Engineering from Shiraz University, Iran, in 2010.


My research interests are in surgical robotics and image-guided therapies. My research typically focuses on the clinical problem first, and work with surgeon collaborators to determine the best devices and theoretical approaches to solve it, which may be new robots or novel algorithms. Our projects typically involve the design and modelling of robotic systems for less invasive and/or more accurate surgery, developing control strategies for inner body manipulation of the surgical robots, and fusing image guidance to help the surgeon perform surgery more accurately. My main research topics are:

  • Surgical Robotics and Image-guided Therapies
  • Continuum and Flexible Robots
  • Mechanics-based Modeling and Simulation
  • Applications of Control Theory in Robotics

There is more information about our research in Lab Website


Recent publications are listed here.



Course description:

  • Applications of robotics and vision; the nature of the problems to be solved; historical overview and current state of the art.
  • Robot actuators and sensors. Parallels to biological systems.
  • Robot control: Open-loop, feed-forward and feedback; PID (proportional integral differential) control.
  • Image formation, transduction and simple processing; thresholding, filtering and classification methods for extracting object information from an image.
  • Active vision and attention.
  • Sensors for self monitoring.
  • General approaches and architectures. Classical vs. behaviour-based robotics. Wider issues and implications of robot research. The course also involves hands-on practicals in which vision and robot systems will be programmed. Relevant QAA Computing Curriculum Sections: Artificial Intelligence; Computer Vision and Image Processing.
    More information.