People

Lecturer in Business Analytics and Data Science

Email: eleni.rozaki@TUDublin.ie

Dr. Eleni Rozaki is a data science specialist and academic with an extensive background in machine learning, business analytics, and AI-driven decision-making. She holds a PhD in Data Science (Computer Science and Informatics) from Cardiff University, and a suite of advanced qualifications from institutions across Europe in quantitative methods, information technology, and digital communication. She teaches a variety of undergraduate business computing and data analytics modules, including: 

• Data Analytics and Visualisation
• Strategic Business Analytics
• Information Analysis for Decision-Making in Business 

Teaching Innovation 

Dr. Rozaki integrates real-world data and live case studies into her teaching, equipping students with practical, in-demand skills. Her work focuses on: 

• Embedding industry-relevant tools into coursework
• Incorporating live datasets and business problems into assignments
• Supervising hands-on, industry-linked projects
• Enhancing global learning through cross-cultural analytics case studies and international research collaborations 

Research Interests 

Dr. Rozaki’s research spans applied AI and data science in business and society, with special interests in: 

• Machine Learning & Data Mining
• Text Analytics & Natural Language Processing
• AI in Consumer Behaviour, Education, and Healthcare
• Predictive Modelling in Finance and Medicine 

Selected Publications 

• Rozaki, E. (2019). Automated Network Optimisation Using Data Mining as Support for Economic Decision Systems (PhD Dissertation, Cardiff University) 

• Dullaghan, C., & Rozaki, E. (2017). Machine learning techniques for dynamic customer segmentation. arXiv 

• Rozaki, E. (2015). Network fault diagnosis using data mining classifiers. IJDKMP, 5(3) 

• Redmond, S., & Rozaki, E. (2017). Bipartite graph- based text classification. Proceedings, Int’l Conference on Advances in Computing 

• Rozaki, E. (2016). Financial predictions using cost- sensitive neural networks. Advanced Engineering Forum 

Industry & Applied Research Experience 

Dr. Rozaki brings extensive real-world experience to her academic practice, having held roles such as: 

• Information Systems Analyst, Barclays (UK)
• Financial Analyst, Symantec (Ireland) 

She has worked with: 

• Telecom partners on customer segmentation via machine learning
• Beaumont Hospital, Dublin on data-driven cancer therapy research 

Her innovations include: 

• Development of automated network fault diagnosis systems
• Application of cost-sensitive neural networks for financial forecasting 

Academic Service & Professional Engagement 

• External Examiner, IADT – Evaluated and advised on curriculum development
• Participated in internal and external reviews for 

TU Dublin’s BA (Hons) Digital Marketing programme 

• Reviewer, International Journal of Data Mining & Knowledge Management Process
• Member, Institute of Commercial Management (ICM)
• Member, Marketing Institute of Ireland (MII) 

Dr. Eleni Rozaki brings together deep technical expertise, practical industry insight, and a passion for data- driven education, making her a key figure in shaping TU Dublin’s analytics and digital transformation agenda.