Mohsen Khadem

Background

I'm a UKRI Future Leaders Fellow and Reader in Robotics at the School of Informatics, University of Edinburgh. I hold degrees in Electrical Engineering, Biomedical Engineering, and Mechanical Engineering. Currently, I am the director of the Surgical and Interventional Robotics Group, an interdisciplinary research lab focusing on the holistic design, development, and clinical validation of healthcare robotic technologies, primarily for surgical interventions. I am also affiliated with the Baillie Gifford Pandemic Science Hub at the Center for Inflammation Research and the Institute of Regeneration and Repair. The hub aims to use human genomics and experimental medicine to rapidly find and test effective drugs to transform the speed of therapeutic innovation.

Research

My research focuses on continuum robotics with primary application in surgical/interventional robotics, areas that are transforming healthcare by enabling more precise and minimally invasive procedures. Collaborating closely with scientists, researchers, biologists, and engineers, I work to enhance current treatment and diagnostic methods. In partnership with end-users and clinical collaborators, we identify the best devices and theoretical approaches to address specific clinical problems. This often involves developing new robot designs, advanced sensors, innovative mechatronic components, and novel algorithms. Our projects aim to improve surgical accuracy by combining image guidance with advanced control strategies. My main research topics are:

• Continuum robotics
• Surgical Robotics and Image-guided Therapies
• Computer Vision and Medical Image Processing
• Mechanics-based Modeling and Simulation
• Applications of Control Theory in Robotics

There is more information about our research on the Lab Website.

Publications

Recent publications are listed here.

Teaching

INTRODUCTION TO VISION AND ROBOTICS

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.