Dr Maryam Abo-Tabik
Maryam is a Lecturer in Computer Science, specialising in deep learning, behavioural modelling, and mobile health applications. With an interdisciplinary approach, she has developed predictive tools for health-related behaviour using machine learning, resulting in widely recognised publications. As a HEA Fellow, she actively contributes to the field through teaching, research, and supervision of advanced projects in health tech and behavioural prediction.
At the University of Central Lancashire, she teaches across multiple modules mostly focused on programming. With a specific research focus on behaviour prediction through AI and sensor data analysis, she engaged in research activities focused on developing new approaches to personalised health interventions. Her role also includes supervising students projects.
She completed a PhD in Computer Science from Manchester Metropolitan University, where her work was on predictive behavioural models using mobile sensor data to support smoking cessation. Before joining us, she held academic and research positions at the University of Liverpool and Loughborough University, building a strong foundation in both research and teaching. She holds recognition as a Fellow of the Higher Education Academy. With a background that includes a Master’s degree in Computer Techniques Engineering and extensive teaching experience in Iraq, she brings a global perspective to her role.
- PhD Computer Science, Manchester Metropolitan University, 2021
- Fellow of the Higher Education Academy, University of Liverpool, 2024
- Associate Fellow of the Higher Education Academy, Manchester Metropolitan University, 2019
- M-Tech Computer Techniques Engineering, College of Electrical and Electronic Engineering Techniques, Baghdad, Iraq, 2012
- BSc Software Engineering, University of Technology, Baghdad, Iraq, 2005
- Machine learning
- Deep learning
- Behavioural prediction models
- Mobile health applications, and Artificial intelligence in healthcare
- Real-time sensor data analysis
- Data science
- Interdisciplinary research in psychology and computer science
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- MAHSC & Health Innovation Manchester (HInM) Cardiovascular Research Domain Award 2024
- 1. Abo-Tabik, M., Costen, N., Darby, J. and Benn, Y., (2019). Decision Tree Model of Smoking Behaviour. In 2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI) (pp. 1746-1753). IEEE.
- 2. Benouis, M., Abo-Tabik, M., Benn, Y., Salmon, O., Barret-Chapman, A. and Costen, N., (2019). Behavioural Smoking Identification via Hand-Movement Dynamics. In 2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI) (pp. 1734-1739). IEEE.
Email: Email:Dr Maryam Abo-Tabik
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