Education#

Cardiff University / Prifysgol Caerdydd#

Doctor of Philosophy (PhD)
2020 - 2024

  • Research Focus:
    Semantic Data Integration for Forest Observatory Applications

  • Overview:
    Conducting innovative research to address challenges posed by research data silos in forest observatories. The work aims to develop semantic data integration frameworks to enable seamless data sharing, interoperability, and analysis across diverse data sources.

  • Contributions and Achievements:

    • Reviewed and compared 13 open data observatories to evaluate data management, data types, and challenges.

    • Proposed semantic web technologies to integrate reseach data silos.

    • Built the Forest Observatory Ontology (FOO) and integrated four wildlife datasets into a knowledge graph with over 6 million RDF triples.

    • Used Google’s TensorFlow and Keras framework to predict elephant movements, achieving 99.04% accuracy, outperforming existing benchmarks of 90.95% and 91.64%.

    • Applied semantic reasoning to predict poaching incidents based on movements data.

    • Adapted the approach for IoT data marketplaces, enabling granualar data queries and selective purchasing for AI training.

    • Published findings in top peer-reviewed journals and presented at international conferences.

Cardiff University / Prifysgol Caerdydd#

Master of Science (MSc) in Data Science and Analytics
2018 - 2019
Grade: Distinction

  • Overview:
    A joint honours degree offered by the School of Mathematics and the School of Computer Science and Informatics.

  • Skills and Knowledge Acquired:

    • Mathematics:

      • Analysing quantitative and qualitative data using advanced statistical methods.

      • Designing algorithms to solve complex mathematical problems and achieve optimal or near-optimal solutions to decision-making challenges.

      • Developing dynamic, interactive, and scalable forecasting applications utilising statistical models, optimisation techniques, and programming tools.

    • Computer Science:

      • Applying data mining and pattern recognition techniques such as supervised and unsupervised machine learning methods.

      • Gaining proficiency in Python programming for data analysis.

      • Developing websites and dashboards to communicate analyses through interactive and dynamic visualisations.

      • Employing distributed and cloud computing technologies to manage and process large-scale data.

The Future university, Khartoum, Sudan#

Bachelor of Science - BS, Computer Engineering

1995 - 2000

  • Officially recognised by the National Recognition Information Centre for the United Kingdom (NARIC) as comparable to British Bachelor degree standard.