- Health and Social Care Modelling
- Software Systems Engineering
About me
I am a Lecturer and Course Leader for the BEng Software Engineering programme at the University of Westminster. In my role as Course Leader, I am responsible for curriculum design and programme development, ensuring strong alignment between academic content, industry practice, and graduate employability. I completed my PhD at Westminster, where my research focused on advancing Process Mining techniques for Natural Language Event Logs, with a strong emphasis on real-world applications.
My research interests sit at the intersection of Process Mining, Data Science, and Artificial Intelligence, with applications in healthcare and business process intelligence. During my doctoral research, I collaborated with Oxleas NHS Foundation Trust, analysing Children and Adolescent Mental Health Services (CAMHS) care pathways to better understand and improve complex service delivery processes.
Before entering academia, I worked as a software engineer and consultant across a range of industries, including running my own consultancy. I designed and implemented business software solutions end-to-end, gaining extensive experience in translating organisational requirements into robust, data-driven systems.
Teaching
I teach and lead modules across undergraduate and postgraduate programmes with a focus on data-driven decision-making and applied software engineering. I am Module Leader for Data Visualisation and Decision Intelligence, where I support students in developing skills in data analytics and the effective communication of insights to technical and non-technical audiences.
Alongside module leadership, I contribute as a tutor in Software Engineering and Data Science modules, and provide academic guidance and pastoral support as a personal tutor. I also supervise undergraduate and postgraduate projects, as well as PhD students.
I am a Fellow of the Higher Education Academy (FHEA) and take a reflective, student-centred approach to teaching. My teaching emphasises authentic, practice-based learning through real-world datasets, industry-relevant tools, and formative feedback, with a strong focus on inclusive learning design and constructive alignment to support students from diverse backgrounds.
Research
My research lies at the intersection of artificial intelligence and business process management, with a particular focus on process mining and process intelligence. I am interested in how AI and data science methods can be used to uncover, analyse, and improve complex organisational processes, especially in settings where data is incomplete, unstructured, or text-based.
A key strand of my work explores the application of process mining to natural language data, addressing scenarios where traditional event logs are unavailable. This includes developing methods and datasets that enable process discovery and analysis from semi-structured textual sources.
Publications
For details of all my research outputs, visit my WestminsterResearch profile.