About me
I am Dr Mohammad Shah, PhD, Lecturer and Foundation Course Leader for Computer Science and Engineering at the University of Westminster.
With over twenty years of experience in computer science, I specialise in software engineering, intelligent systems, and cybersecurity. In my role, I lead the foundational computer science course, supporting students in learning the fundamentals of programming, databases, and core computing principles.
My research focuses on automated planning and knowledge engineering, exploring how intelligent systems can reason, represent domain knowledge and make decisions autonomously. As an AI research consultant, I also apply my expertise in machine learning and automated planning to help organisations harness technology for real-world impact.
I am a Fellow of the Higher Education Academy and a Member of both the British Computer Society and the IEEE, reflecting my commitment to teaching excellence and professional standards. I hold a PhD in AI from the University of Huddersfield and have received multiple grants and scholarships to present my work at international events.
Teaching
I teach a broad range of computer science courses, covering programming (e.g., Python, Java), databases (relational and NoSQL), business information systems concepts, and key foundational topics (algorithms, data structures, software engineering). I supervise undergraduate and postgraduate project work, guiding students from topic selection through research or system development to final delivery.
My teaching emphasises practical problem-solving, disciplined project practice and transferable skills such as teamwork, project management and reflective learning. I support students through workshops, lab sessions, and one-on-one mentoring. I also integrate my expertise in automated planning and knowledge engineering into the curriculum, enhancing technical modules with insights into how intelligent systems reason and act.
Research
I am a researcher in artificial intelligence (AI) with a focus on automated planning and knowledge engineering. My work has explored how intelligent systems can acquire and represent knowledge, build domain models, and generate decision-making plans that adapt to dynamic environments. I have applied these ideas in real-world domains such as traffic incident management and cyber-physical systems, producing a body of work reflected in publications and citations across numerous collaborative projects.
Through this research I aim to bridge theoretical foundations and applied outcomes, advancing both the modelling of intelligent agents and their deployment in practical systems that respond autonomously to changing conditions.
Publications
For details of all my research outputs, visit my WestminsterResearch profile.