PROFILE SUMMARY

Mr. Hammad Ahmed Abbasi is a researcher and academic professional with a strong focus on research, programming, and data-driven analysis, aiming to bridge the gap between computing education, applied research, and real-world software development. He is currently serving as a Lecturer in the Department of Software Engineering at Shifa Tameer-e-Millat University, where he is actively involved in teaching, research supervision, and curriculum-based academic activities. He holds a Master’s degree in Data Science from Shifa Tameer-e-Millat University and a Bachelor’s degree in Computer Science from Pir Mehr Ali Shah Arid Agriculture University. His academic background provides a strong foundation in programming, data analysis, and computational research. In addition to his academic career, Mr. Hammad has extensive industry experience, having worked remotely with multiple international companies as a Web Developer and Mobile Application Developer. He has also delivered numerous online programming tutorials, demonstrating his commitment to practical skill development and modern teaching methodologies. His research interests center on Retracted Articles, where he focuses on identifying dangerous or misleading research publications, analyzing their causes, and studying their impact on the academic and scientific community. His work aims to contribute to research integrity, scholarly transparency, and evidence-based decision-making. With a balanced combination of teaching, industry exposure, programming expertise, and research orientation, Mr. Hammad continues to work towards advancing computing education and responsible research practices, while mentoring students to meet both academic and industry standards.

RESEARCH AREAS / INTERESTS

1. Retraction Articles
   2. Machine Learning
   3. Scientific Article Classification using BERT / SciBERT / RoBERTa
   4. Ensemble Learning for Academic Text Classification
   5. Pattern Discovery in Retracted vs Non-Retracted Articles
   6. Visual Analytics of Retraction Trends (Year-wise / Journal-wise)