Education
Teaching
Projects, systems thinking, and real-world practice across disciplines.
Teaching
I teach across undergraduate, postgraduate, and degree apprenticeship provision, with experience spanning business, engineering, and computing. My teaching is student-centred, inclusive, and practice-led, connecting theory with real-world challenges in AI, data analytics, control and automation, database systems, and scalable computing. Research-led and studio-style delivery also spans digital and analogue systems, programming (Python), mathematics, data/AI, and professional skills for industry-ready practice.
Module Leadership
- Deriving Business Value Using Data Analytics
- Digital Control and Automation
- Database Engineering
- Machine Learning
- Scalable Systems
Broader module themes
- Analogue and digital systems
- Programming (Python)
- Mathematics for AI and control
- Data/AI for engineering systems
- Professional skills for engineers
Curriculum Development and Educational Innovation
My curriculum work focuses on designing and enhancing learning experiences that are academically rigorous, inclusive, and professionally relevant. Through module and course leadership, I have contributed to curriculum review, assessment design, programme coherence, and interdisciplinary education across business, engineering, and computing.
Supervision
I supervise undergraduate, postgraduate, and doctoral research and project work, including one completed PhD and several ongoing doctoral supervisions. My approach emphasises critical thinking, methodological rigour, and applied impact — including successful completion to graduation and a strong portfolio of research projects at MSc and UG level.
- Module leadership and delivery links theory to deployable practice across the leadership portfolio and broader engineering and computing teaching.
- Assessments emphasise rigorous methods, responsible AI use, and industry-relevant problem framing.
Teaching approach
- Learning by doing: students build understanding through modelling, experimentation, simulation, and project work.
- Coaching and facilitation: guided support as teams test ideas, refine solutions, and build technical judgement.
- Interdisciplinary work: business, engineering, and computing ideas taught as connected practice with control, automation, computation, and systems thinking.
- Professional outputs: reports, simulations, presentations, prototypes, and applied analysis.
- Feedback-rich learning: structured feedback that supports technical growth, confidence, and professional readiness.
Student development
I aim to help students become confident problem-solvers who can connect theory with implementation. This includes teamwork, technical communication, analytical thinking, reflective practice, and readiness for professional environments across disciplines.