Dr Anousheh Ramezani
Lecturer in Artificial Intelligence
- Phone
- +44 (0)1473 339042
- a.ramezani@uos.ac.uk
- School/Directorate
- School of Business, Arts, Social Sciences and Technology
- Anousheh Ramezani ORCID
-
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She holds a PhD in Computing with a specialism in Artificial Intelligence from Ulster University. Her doctoral research was funded by BT Group and Invest NI. She also holds BEng and MSc degrees in Electrical and Telecommunications Engineering. She holds a Global Talent endorsement from the Royal Academy of Engineering in acknowledgement of her Exceptional Talent in Engineering and Technology. At Ulster University, she supported the delivery of modules in Artificial Intelligence, Deep Learning, Systems Security, and Computer Technology, and completed the First Steps to Teaching programme (AFHEA). Prior to joining the University of Suffolk, she was a Teaching Fellow at Durham University, contributing to modules in Algorithms and Data Structures, Artificial Intelligence, and Security Engineering. She also supervised MSc Business Analytics projects, supported the Sutton Trust summer school programme, and contributed to widening participation activities at Durham University.
She teaches across a broad range of undergraduate and postgraduate modules in Artificial Intelligence, data science, databases, programming, and cybersecurity. Her teaching includes modules such as Relational Databases, SQL and NoSQL, Data Mining and Statistical AI, AI and Data Science Applications, Advanced Machine Learning, Information Systems Engineering, and Blockchain, AI and Secure Systems in Finance. She is also actively involved in outreach and widening participation initiatives, including delivering ChriSTEMas lectures at BT’s Adastral Park to school students from across the East of England.
She has supervised numerous MSc research projects in areas including Machine Learning, computer vision, healthcare AI, autonomous vehicles, business analytics, sports data analysis, and space applications. Topics have included diabetic retinopathy detection using Deep Learning, exoplanet detection with machine learning, sales forecasting, player similarity modelling in football analytics, and lane detection for autonomous vehicles.
Her research interests include:
-Application of Artificial Intelligence (AI) within the field of cybersecurity (exploring how Machine Learning, Deep Learning, and intelligent automation can be used to detect, prevent, and respond to evolving cyber threats).
-Application of Artificial Intelligence (AI) in Financial Technology (FinTech), with a focus on the foundations of AI and its transformative role in modern financial services, including robo-advisors, credit scoring models, algorithmic trading for data-driven market strategies, and fraud detection systems.
-Developing Self-Adaptive models for business processes optimisation. This includes the application of data-driven automation, predictive analytics, and intelligent decision-support systems within enterprise environments, with particular interest in large-scale industrial applications such as those in Telecommunications and digital services at BT Group.
-Pedagogical Innovation in Computing Education
She is a Fellow of the Higher Education Academy (FHEA) and has completed the Postgraduate Certificate in Academic Practice (PgCAP) at University of Suffolk.