Raghad Al-Shabandar

The Application of Gaussian Mixture Models for the Identification of At-Risk Learners in Massive Open Online Courses

Andy Laws, Thar Baker, Abir Hussain, 2018, 2018 IEEE Congress on Evolutionary Computation (CEC).

Detecting At-Risk Students With Early Interventions Using Machine Learning Techniques

Abir Jaafar Hussain, Raghad Al-Shabandar, Robert Keight, 2019, IEEE Access.

Machine learning approaches to predict learning outcomes in Massive open online courses

Andy Laws, Abir Hussain, Raghad Al-Shabandar, 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

Lossy and Lossless Video Frame Compression: A Novel Approach for High-Temporal Video Data Analytics

Thar Baker, Abir Jaafar Hussain, Panos Liatsis, 2020, Remote. Sens..

A deep gated recurrent neural network for petroleum production forecasting

Panos Liatsis, Raghad Al-Shabandar, Abir Hussain, 2021 .

Analyzing Learners Behavior in MOOCs: An Examination of Performance and Motivation Using a Data-Driven Approach

Abir Jaafar Hussain, Raghad Al-Shabandar, Robert Keight, 2018, IEEE Access.

Towards the Differentiation of Initial and Final Retention in Massive Open Online Courses

Andy Laws, Abir Hussain, Raghad Al-Shabandar, 2017, ICIC.

The Application of Artificial Intelligence in Financial Compliance Management

Gaye Lightbody, Fiona Browne, Raghad Al-Shabandar, 2019, AIAM.