- Software Systems Engineering
About me
Dr Natalia Yerashenia is a Senior Lecturer in Data Science & Analytics at the University of Westminster, with a multidisciplinary background spanning Engineering, Finance, and Computer Science. She holds BA and MA degrees in Economics and Production Engineering, an MSc in Finance and Accounting, a PGCert in Higher Education, and a PhD in Computer Science, and is a Fellow of the Higher Education Academy (FHEA).
Her research develops ontology-guided artificial intelligence, combining ontologies, knowledge graphs, and graph databases with machine learning, GraphRAG, and large language models to build transparent, trustworthy, and explainable AI systems. Her broader expertise spans Applied Mathematics, Applied AI, connected and semantic data analytics, and predictive computational modelling, with applications across finance, business, technology, education, and healthcare.
Alongside her research, Natalia leads modules and contributes to programme development as a Module Leader and Course Co-Leader for the BSc Computer Science programme, and she supervises doctoral, postgraduate and undergraduate researchers. She is passionate about teaching, combining strong theoretical foundations with practical application to prepare students for today's data-driven world. A founding contributor to the Westminster AI Network, she has delivered funded, collaborative research with partners, including the Alan Turing Institute.
She actively welcomes PhD students, researchers and industry partners interested in collaborative projects that advance innovation in Data Science & Analytics.
Teaching
Currently involved in the following:
- BSc Computer Science – Course Co-Leader
- Level 4 Mathematics for Computing – Module Leader
- Level 7 Big Data Theory and Practice – Module Leader
- Level 5 Software Development Group Project – Seminar Tutor
- Level 7 Web and Social Media Analytics – Seminar Tutor
- Level 6 Computer Science Final Year Project – Project Supervisor
- Level 7 Data Science & Analytics MSc Project – Project Supervisor
Research
PhD Thesis – Generic Architecture for Predictive Computational Modelling with Application to Financial Data Analysis: Integration of Semantic Approach and Machine Learning.
Natalia's current research programme focuses on ontology-guided and explainable AI — knowledge graphs, ontologies, GraphRAG, semantic technologies and predictive computational modelling — with applications in education, healthcare and finance.
Publications
For details of all my research outputs, visit my WestminsterResearch profile.