Mr. Abdul Qayum , University of Limerick , Ireland
Abdul Qayum is a dedicated PhD scholar at LERO, the SFI Research Centre for Software at the University of Limerick (UL), Ireland. His current research focuses on the RADeLE (Reference Architecture for Deep Learning Environment) project sponsored by Huawei. He has innovatively designed a framework to assist researchers, software developers, and software architecture engineers in selecting the optimal tools and techniques for software architecture recovery. Abdul has also introduced a comprehensive taxonomy based on 10 dimensions, enhancing the understanding and application of software architecture recovery methodologies.
Profile :
Education:
- PhD in Designing a Reference Architecture for Deep Learning Environments, LERO, University of Limerick, Ireland (Ongoing)
- MS in Computer Science, COMSATS University Islamabad, Pakistan, 2019-2021
- Thesis: Multi-Perspective Source Code Analysis Support for Software Developer through Fine-Granular Level Interactive Code Visualization
- BS (Hons.) in Information Technology, University of Sargodha, Pakistan, 2013-2016
Work Experience:
- Associate Lecturer, National College of Ireland (NCI), Dublin, Ireland
- Courses taught include Cloud Machine Learning and The Computing Industry for MSc and BSc students.
- Supervised 12 MSc theses.
- Lecturer, University of Sialkot, Pakistan
- Taught information technology and computer science modules to BS and MSc classes.
- Supervised Final Year Projects (FYPs) and advised student batches.
- Lecturer, Saed Islamic College, Pakistan
- Taught various computer science modules, including compiler construction, operating systems, and data mining.
- Software Developer, iParagons Tech, Pakistan
- Developed applications such as Stress Manager (Java) and SUDO-Search Yours and Display Others (Swift).
- Conducted source code analysis and architectural extraction for large-scale systems.
Research Experience:
- Developed FineCodeAnalyzer for bug/feature location using knowledge graph-based analysis, improving developer efficiency and accuracy.
- Published research articles in IEEE Access and presented findings at international conferences.
Technical Skills:
- Expertise in Python, Java, C++, TensorFlow, Scikit-learn, Pytorch, Neo4j, D3, PyDriller, Pandas, Numpy.
- Proficient in source code analysis, machine learning, natural language processing, and graph semantics.
Publication Top Notes:
Citation : 4
Citation : 4
Citation : 3