Dr. Islam Zada, International Islamic University, Pakistan
Dr. Zada is an Assistant Professor in the Department of Software Engineering at International Islamic University (IIU), Islamabad, with a Ph.D. in Computer Science from the University of Peshawar. His research focuses on software defect prediction and clustering algorithms, with influential publications such as “Software defect prediction employing BiLSTM and BERT-based semantic feature” in Soft Computing and “Analysis of Simple K-Mean and Parallel K-Mean Clustering” in Scientific Programming. His expertise extends to teaching a broad range of software engineering courses, including Agile and Sustainable Software Engineering. Dr. Zada’s contributions reflect a strong commitment to advancing sustainable software practices and enhancing software performance analysis.
Suitability for the Award
Dr. Islam Zada is highly suitable for the Research for Young Scientist Award due to the following reasons:
- Advanced Academic Background: Dr. Zada’s academic journey, culminating in a Ph.D. in Software Engineering, underscores his deep understanding of and commitment to the field.
- Innovative Research: His Ph.D. research on an ontology-based integrated approach for sustainable software development is both timely and relevant, reflecting a focus on sustainability in software engineering, a crucial area in today’s tech landscape.
- Teaching and Mentorship: Dr. Zada has a rich teaching portfolio, having taught a wide range of software engineering and computer science courses at multiple institutions. His role as an Assistant Professor demonstrates his leadership and dedication to educating the next generation of software engineers.
- Impactful Publications: Dr. Zada has contributed to high-impact research, as evidenced by his publications. His work on software defect prediction using advanced AI techniques like BiLSTM and BERT is particularly noteworthy, highlighting his ability to apply cutting-edge methods to solve complex problems in software engineering.
- Young but Experienced: Despite his relatively recent entry into academia, Dr. Zada has amassed significant experience and accomplishments, making him a standout young researcher in his field.
Educational Background:
Dr. Zada holds a Ph.D. in Computer Science with a specialization in Software Engineering from the University of Peshawar, and a Master’s in Software Engineering from the same institution. His academic foundation is complemented by a Master’s and Bachelor’s degree in Computer Science from the University of Malakand. His thesis work on “An Ontology-Based Integrated Approach for Sustainable Software Development” reflects his commitment to advancing sustainable software engineering practices.
Professional Experience:
Dr. Zada has a diverse range of teaching and research roles, including his current position as an Assistant Professor in the Department of Software Engineering at International Islamic University (IIU), Islamabad. He has previously served as a lecturer at IIU, Kohat University of Science & Technology, and the University of Peshawar. His experience spans various institutions and includes roles such as Research Associate and IT Trainer, showcasing his broad expertise in software engineering and IT.
Courses Taught:
Dr. Zada has taught a wide array of courses including Data Structures, Software Project Management, Software Engineering & Re-engineering, Agile Software Engineering, and Green and Sustainable Software Engineering. His involvement in these courses indicates a strong commitment to educating the next generation of software engineers.
Research and Teaching Impact:
His research and teaching roles have had a significant impact, evidenced by his publications and contributions to the field. His research on software defect prediction and clustering algorithms has been well-received in the academic community, reflecting his role as a leading young scientist in software engineering.
Publication Top Notes:
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Title: Software Defect Prediction Employing BiLSTM and BERT-Based Semantic Feature
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Title: Analysis of Simple K-Mean and Parallel K-Mean Clustering for Software Products and Organizational Performance Using Education Sector Dataset
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Title: Software Architecture for Pervasive Critical Health Monitoring System Using Fog Computing
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Title: Evaluation of Software Birthmarks Using Fuzzy Analytic Hierarchy Process
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Title: Analysis of Service-Oriented Architecture and Scrum Software Development Approach for IIoT