Mohammad graduated from the University of Nottingham, Malaysia, with a Master of Engineering (MEng.) in Electrical and Electronic Engineering.
In the past Mohammad has worked on projects designing trajectory optimisation algorithms for multiple, heterogeneous, Unmanned Aerial Vehicles (UAVs) as well as Reinforcement Learning for collaborative tasks between multiple UAV groups.
Mohammad is currently based at the Control Systems Research Group in the Wolfson School of Mechanical, Electrical and Manufacturing Engineering, Loughborough University.
Mohammad is researching safety-critical controllers for single-track, powered two-wheeler vehicles (with a key focus on motorcycles). Recently, the increased adoption of motorcycles as a popular means of transport has also seen a disproportionate increase in fatalities related to motorcycle accidents as well. Improved safety in motorcycles on the road is therefore an increasing concern, with various active and passive safety and autonomy systems in motorcycles falling notably behind other vehicles in development and implementation.
Currently, this research involves an investigation into motorcycle path planning and trajectory optimisation as a means to enforce safety-critical control. Motion planners must account for the unique dynamic constraints presented in motorcycles and powered two-wheelers that pose a challenge in the stability and control of these systems. The end goal will be to design real-time, general-purpose controllers and motion planners for autonomous or rider-assistance motorcycles, that will hope to improve safety for riders on the road.