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"Research-driven. Engineer-minded. Always learning." I am an AI researcher and software developer specializing in Computer Vision, Medical Image Analysis, and Explainable AI (XAI). My journey bridged the gap between robust software engineering and advanced machine learning research. Currently, I focus on building trustworthy, transparent, and clinically interpretable AI systems that solve real-world problems. |
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1. Automated Detection and Classification of Renal Abnormalities using a Hybrid Deep Learning Framework and XAI
Developing a hybrid deep learning framework for automated renal CT image classification using Explainable AI (Grad-CAM and SHAP) to improve model transparency and clinical interpretability.
2. A Hybrid AI-Based Architecture for Vehicle Safety and Accident Prevention in Bangladesh
Developing a computer vision-based intelligent transportation system (ITS) for real-time vehicle and hazard detection under complex, unstructured road conditions in Bangladesh.
3. An Interpretable Hybrid Artificial Intelligence Framework for Automated Cardiovascular Disease Diagnosis
Architecting an interpretable clinical decision support system (CDSS) for early cardiovascular risk prediction, focusing on quantitative feature importance to verify clinical guidelines.
4. Automated Detection of Fake Job Advertisements in Bangladesh via Machine Learning Approaches
Developed machine learning models for detecting fraudulent online job advertisements. Presented at the ECCT Conference and published in an international Taylor & Francis book series.
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5. Sentiment Analysis & Classification Optimization using Machine Learning
Evaluated text preprocessing pipelines and hyperparameter tuning strategies to optimize multi-class sentiment classification performance.
      
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