Staff profile
Overview
Tahani Aljohani
Biography
Biography
Mrs Aljohani is a Ph.D. researcher and a member of the Innovative Computing Group at the Computer Science Department, Durham University. Her primary research interest is NLP and ML classification/predication tasks based on supervised/unsupervised learning via deep learning architectures.
Research Interests
- Natural Language Processing
- Data Science
- Machine Learning
- Deep Learning
Publications
Chapter in book
- Alrajhi, L., Pereira, F. D., Cristea, A. I., & Aljohani, T. (2022). A Good Classifier is Not Enough: A XAI Approach for Urgent Instructor-Intervention Models in MOOCs. In M. Mercedes Rodrigo, N. Matsuda, A. I. Cristea, & V. Dimitrova (Eds.), Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium (424-427). Springer Verlag. https://doi.org/10.1007/978-3-031-11647-6_84
- Aljohani, T., Cristea, A. I., & Alrajhi, L. (2022). Bi-directional Mechanism for Recursion Algorithms: A Case Study on Gender Identification in MOOCs. In M. Mercedes Rodrigo, N. Matsuda, A. I. Cristea, & V. Dimitrova (Eds.), Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners’ and Doctoral Consortium (396-399). Springer Verlag. https://doi.org/10.1007/978-3-031-11647-6_78
- Aljohani, T., & Cristea, A. I. (2021). Training Temporal and NLP Features via Extremely Randomised Trees for Educational Level Classification. In A. I. Cristea, & C. Troussas (Eds.), Intelligent Tutoring Systems: 17th International Conference, ITS 2021, Virtual Event, June 7–11, 2021, Proceedings (136-147). Springer Verlag. https://doi.org/10.1007/978-3-030-80421-3_17
Conference Paper
Presentation