PROFILE SUMMARY

Muhammad Shaban Qabil is an emerging academic and data science researcher who integrates expertise in computer science, artificial intelligence, and scientometrics analytics. With a strong background in software development and advanced skills in machine learning, deep learning, NLP, and data engineering, he focuses on building data-driven frameworks for researcher ranking and academic impact assessment. His professional journey spans university teaching, curriculum development, academic committee engagements, and industry roles in ML engineering, Android development, and full-stack application design, allowing him to bridge theoretical concepts with real-world implementations. He has taught core computing subjects, mentored students, contributed to assessment processes, and delivered practical solutions including intelligent chatbots, churn prediction systems, automated document generation, and AI-based medical analysis tools. As a gold medalist at both undergraduate and postgraduate levels, he consistently demonstrates academic excellence, analytical depth, and a commitment to advancing research, improving academic processes, and fostering meaningful technological innovation.

RESEARCH AREAS / INTERESTS

1. Scientometrics
   2. Researchers Assessment
   3. Machine Learning / Deep Learning
   4. Data Science