• United Kingdom

Accepting PhD Students

PhD projects

Using Machine Learning and Deep Learning in Manufacturing. NLP. Connectivity and 5G. Fake News Classification and Clustering Documents. Digital Twin. MTConnect and Robotic Operating System.

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Personal profile

Personal Statement

Personal Statement

 

  • Member of the NMIS's SME Engagement Team serves as SME Engagement Advisor. The role involves raising awareness of the benefits of digital manufacturing technologies amongst Scottish manufacturing SMEs and smart supply chains, demonstrating available technologies and solutions, and providing links into appropriate support networks.


     Shawki Al-Dubaee holds BEng in Computing Technology, MSc in Computer Engineering, MBA in IT and PhD in Computer Engineering. He currently works as an SME Advisor National Manufacturing Institute Scotland at the University of Strathclyde. He previously served as a Partnership Development Leader and representative Advanced Forming Research Centre- NMIS on the Manufacturing Industry Digital Innovation Hubs consortium. Al-Dubaee delivered successfully several projects, especially the MIDIH project, which was the biggest strategic project in the Digital Manufacturing team and funded by Horizon 2020. He worked as a teaching assistant and an Honorary Research Associate at the School of Computing Science at the University of Glasgow.

    From 2011 to 2015, Al-Dubaee was an Assistant Professor at the Communication and Computer Engineering Department of the Faculty of Engineering and Information Technology, Taiz University (Yemen), and Head of the Information Technology Department (Nov 2011 to Sep 2014) as well as Head of the Computer Networks and Distributed System Department, CNDS (Sep 2012 to Sep 2014). While at Taiz University, Al-Dubaee also worked as a Team leader within the Quality Improvement Program for Computer Networks and Distributed System program, sponsored by the World Bank and the Ministry of Higher Education (Jul 2013 to Mar 2015).

    Al-Dubaee has good experience as a Full Stack Web Developer using HTML5, CSS, JavaScript, ES6, Nodejs, Express, Passportjs, React, React Native, Docker, NodeRED, TensorFlow and PyTorch frameworks.

    PhD Supervision: 

    Fathi Sharadah - Anomaly detection for Machine Remote Monitoring System. 

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