projects

My Projects

I have worked on and developed a diverse range of Artificial Intelligence, Machine Learning, Deep Learning, and intelligent computing projects focused on solving real-world problems. My projects include AI-based healthcare and medical diagnosis systems, brain tumor detection using deep learning, skin lesion analysis, thyroid cancer prediction using Explainable AI, cardiovascular disease prediction, intrusion detection, and AIoT-based smart traffic management. Through these projects, I have applied advanced techniques such as ensemble learning, transfer learning, neural networks, optimization algorithms, and Explainable AI (XAI) to develop intelligent, accurate, and interpretable solutions. These projects reflect my commitment to combining research, innovation, and practical implementation to address complex challenges through modern AI technologies.

My latest projects

I am working on projects and research in areas such as Artificial Intelligence, Machine Learning, Deep Learning, Explainable AI, Computational Intelligence, Healthcare AI, Cybersecurity, IoT, Smart Cities, Computer Vision, Signal Processing, and Data Analytics. My research interests include intelligent intrusion detection, blockchain-based network security, cardiovascular and cancer prediction, medical image analysis, brain tumor and skin lesion classification, traffic congestion control, plant disease detection, diabetes and air-quality prediction, student engagement analytics, emotion recognition, cryptography, and time-series forecasting. My work focuses on developing optimized, interpretable, and practical intelligent systems that can address real-world challenges.

Explainable AI for Thyroid Cancer Prediction

An optimized ensemble machine learning framework for thyroid cancer prediction, using Explainable Artificial Intelligence (XAI) to provide transparent and interpretable clinical insights

AIoT-Enabled Traffic Congestion Control System

An Artificial Intelligence of Things (AIoT)-based smart city project that uses deep neural networks and machine learning to analyze traffic conditions and support intelligent traffic congestion control. The project combines AI, IoT, and smart city technologies for real-time traffic management.

Intelligent Cardiovascular Disease Prediction

A machine learning-based cardiovascular disease prediction system enhanced through Gradient Descent Optimization, designed to improve the accuracy of automated heart disease diagnosis.

Explainable Hybrid Deep Learning for Skin Lesion Analysis

A hybrid deep learning framework for skin lesion segmentation and multi-class classification, incorporating Explainable AI (XAI) to improve the interpretability of medical predictions.

Advancing Innovation Through
Artificial Intelligence,
Machine Learning,
and
Intelligent Solutions.
Contact Me