Dr Bing Zhai

Lecturer

Department: Computer and Information Sciences

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.

Website: https://bzhai.github.io/

Google Scholar: Click here

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Key Publications

Please visit the Pure Research Information Portal for further information
ConvBoost: Boosting ConvNets for Sensor-based Activity Recognition, Shao, S., Guan, Y., Zhai, B., Missier, P., Plötz, T. 12 Jun 2023, In: Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
Ubi-SleepNet: Advanced Multimodal Fusion Techniques for Three-stage Sleep Classification Using Ubiquitous Sensing, Zhai, B., Guan, Y., Catt, M., Ploetz, T. 30 Dec 2021, In: Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies
Making sense of sleep: Multimodal sleep stage classification in a large, diverse population using movement and cardiac sensing, Zhai, B. 15 Jun 2020
The future of sleep health: a data-driven revolution in sleep science and medicine, Zhai, B. 23 Mar 2020

Qualifications

Computer Science PhD

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