Publications & Research

Here is a detailed list of my peer-reviewed publications, conference papers, and collaborative research contributions across domains like software modeling, AIoT systems, and sustainable software engineering.

📘 Journal Publications

I have contributed to several peer-reviewed international journals, focusing on formal methods, model transformation, and sustainable software systems.

IEEE Access (2024)

Dynamic Property Preservation in AIoT: A Machine Learning Approach for Efficient Model Transformation

Elsevier – Journal of Systems and Software (2025, In Press)

A Systematic Literature Review on Model Transformation and Property Preservation

MDPI Energies (2020)

Smart and Agile Manufacturing Framework for AI-based Transformation in the Automotive Industry

International Journal of Web Engineering and Technology (2024)

Beyond Functionality: Designing an RDF Engine for Semantic-Driven Web Data Representation

Smart and Agile Manufacturing Framework

MDPI Energies – A traceability-based agile model to improve flexibility and performance in automotive manufacturing.

Traceability Framework for Model Transformations

Presents a meta-model-driven traceability framework to support bi-directional model transformations in CMMI Level 2-compliant software enterprises.

AI in Pharmacy and Clinical Care

Explores AI-driven innovations that enhance drug safety, precision treatment, and operational efficiency in pharmacy and clinical healthcare settings.

Smart Neuro Diagnosis Using Hierarchical Deep Learning

Proposes a CNN-based IoMT system for accurate brain tumor detection and classification into four categories with 96.54% accuracy.

Smart Aviation with ML-Based Delay Prediction

Presents a secure, collaborative ML platform for predicting flight delays using supervised learning on real-time aviation data.

Fine Decision Tree for Intrusion Detection

Compares supervised ML models for network intrusion detection, highlighting fine Decision Tree’s 99.4% accuracy on NSL-KDD and NID datasets.

AI-Driven Soil Nutrient Prediction for Cotton Farming

Uses advanced machine learning models to predict key soil nutrients (N, P, and K), enabling precision fertilizer management and sustainable cotton cultivation.

AI in Higher Education: Teaching, Engagement, and Learning Outcomes

Examines how AI tools enhance teaching effectiveness, student engagement, and learning achievement while addressing ethical, governance, and academic integrity challenges.

🏛️ Conference Papers

Presenting at international conferences has allowed me to share my research with global academic communities, receive critical feedback, and stay connected with emerging trends in software engineering and formal methods.

ACM SPLC 2024 (New York, USA)

Goal Modeling for Preserving NFRs in Software Product Lines using Meta-models

IEEE International Requirements Engineering Conference (RE 2021)

Property Preservation and Traceability in Requirement Engineering

Model-Oriented Traceability for SMEs

Proposes a model-driven framework to improve bi-directional requirements traceability in CMMI Level 2 software organizations.

Preserving NFRs in Goal Models

Introduces a meta-model-based framework to maintain non-functional requirements across software product lines in goal-oriented modeling.

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Let’s Connect

For academic collaborations, research inquiries, or student guidance, feel free to reach out