Dr Hasan Shaheed
PhD (Sheffield), PGCAP (London), SFHEA, MIEEE, CEng, MIET, NTF

Research Overview

Interests

Design, models development, control and optimisation of autonomous, robotics and renewable energy systems using traditional, artificial intelligence (AI) and machine learning (ML) approaches. Application areas include,

[1] Aerial Robotics and Solar Aerial Robotics for inspection and monitoring
[2] Medical Robotics: Capsule robot for GI tract inspection, Surgical robots, Retractor for surgery
[3] Assistive technologies: prosthetics  and elderly care robots
[4] Robotics for remote inspection and handling: Leader-follower robot and pipe-inspection robot
[5] Renewable Energy Systems: PV, Wind turbine, Osmotic Power/Blue Energy and hybrid technologies
[6] Water Treatment: Desalination/Water Treatment powered by hybrid renewable energy technologies
[7] Expert systems with application to disease prognosis and classification

AI/ML approaches Dr Shaheed investigates and uses in his research include, deep learning, reinforcement learning neural networks, fuzzy logic, biologically inspired optimisation techniques: GAs, Whale Optimisation, Grey Wolf Optimisation, Cuckoo optimisation algorithm, Particle swarm, Ant colony, Bee colony etc.

Output and impact: Published a over 80 refereed research articles in quality journals and conference proceedings. According to ‘Web of Knowledge/Science’ his h-index is 20 (24, Scopus; 28, Google Scholar) with an average citation over 47 per year. Design and experimental validation of a novel locomotion concept for an endoscopic capsule robot resulted in a patent at PCT stage and an international patent publication (PCT/EP2021/075342, WO 2022/058354/A1). He was invited to submit an application for the Eni Award, one of the most prestigious awards in the field of renewable energy, due to my contribution to the field. The proof of concept ‘solarcopter’, prototype, the world first quadrotor to fly with solar power only, received immense media attention. Dr Shaheed received the Innovation Award, Proof of Concept Award, Engagement and Enterprise Award, Impact Acceleration Account Award, Barts Innovations in Healthcare Award and HEFCE Med Tech Super Connector Award from Queen Mary Innovation (QMI) due to the commercial potential of several of his research outputs.

***Potential students willing to pursue a PhD in any of the fields mentioned above are encouraged to contact me.