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Personal profile


I am a Lecturer in Computer Science. My research agenda is to develop practical AI tools to solve time-series data challenges in real-world applications.  I am particularly interested in time series data analysis, e.g., biosignal analysis, computational behaviour analysis and healthcare applications. I am also interested in AI for good, computer vision and audio/speech analysis. 

In essence, it is to model the practical problems using mathematical languages and develop machine learning algorithms for the optimal solution, bridging the gap between signal/data and human-understandable knowledge. In particular, I have experience developing ML/DL algorithms for biosignal data-based applications in physical behaviour assessment and health and well-being monitoring. 

I was a research associate at the School of Computing at Newcastle University, working on the IDEA-FAST project (€40 million) to identify digital endpoints and biomarkers of sleep disturbance and fatigue. During this time, I obtained my PhD in data science for healthcare from the School of Computing, Newcastle University. 

At Northumbria University, I currently conduct sleepiness and fatigue research using machine learning methods and collaborate with more than a dozen research institutions on the IDEA-FAST project.


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Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being

Education/Academic qualification

Computer Science, PhD, Towards Automated Sleep Stage Assessment Using Ubiquitous Computing Technologies (Newcastle University)


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