- Email: firstname.lastname@example.org
- Thesis title: Deep Learning and Distributional Semantics for the Quran
- Supervisors: Professor Eric Atwell, Dr Mohammad Ammar Alsalka
- I currently work as a lecturer in the Department of Information and Computer Sciences at Jouf University.
- I joined the University of Leeds as a Ph.D. student in October 2018. During my study, I investigate artificial intelligence methodologies applied to religious texts. My research aims at promoting the acquisition of knowledge from the Quran and potentially delivering robust resources to learn and teach the sacred text.
My research aims at promoting understanding of the Quran and probing the concealed knowledge within it. With Artificial Intelligence's rise and the latest deep learning revolution, this task became much more feasible. Using machine learning and deep learning approaches, we aim to generate a robust representation of the text. Such representation can be powerful when it comes to an understanding and potentially reveals embedded patterns and details that frame a meaningful semantic structure of the text.
My Ph.D. research investigates AI applied to text and exploits NLP methods to analyze and probe texts' underlying knowledge. I use ML/ DL models with NLP techniques to examine the semantic similarity task and extract the meanings and concepts from the Quran. I use embeddings techniques such as Doc2vec and BERT to create rich sentence embeddings of the Quran verses and provide informative input to ML/DL models. I then train classifiers and Neural networks on top of the derived vectors for classification, regression, and textual similarity.
- ME in Software Engineering. University of Colorado Springs, USA, 2015