🎓 Aspiring AI researcher | Focused on Biomedical Machine Learning & Computer Vision
I am a Computer Science graduate passionate about applying AI to healthcare challenges.
My motivation comes from personal experience with a misdiagnosed skin condition, which taught me how critical accurate and accessible diagnostics are. Since then, I’ve been committed to using machine learning to improve clinical decision support systems.
- Deep learning and computer vision for biomedical diagnostics (medical imaging, disease detection, biometric systems)
- Machine learning for healthcare data, including patient records, biosignals, and predictive modeling of outcomes
- Robust and generalizable AI through cross-domain validation, transfer learning, and model adaptation
- Explainable and trustworthy AI to improve reliability of clinical decision support systems
- Dental Biometric Identification System – Final Year Project using VGG16 for biometric identification from dental records (forensics & disaster recovery)
- Breast Cancer Classification – ML models on clinical data for tumor diagnosis
- Heart Disease Prediction – Ensemble ML models for cardiovascular risk prediction
- Credit Card Fraud Detection – Handling imbalanced datasets for anomaly detection
- Food Vision AI – Real-time image classification system using EfficientNetB7, deployed with Flask
- Programming & Tools: Python, SQL, Git, C++
- ML/DL Frameworks: scikit-learn, TensorFlow, Keras, PyTorch
- Architectures: CNNs, RNNs, LSTMs, Transfer Learning
- Data & Evaluation: Data preprocessing, visualization, cross-domain validation, model interpretability
- Specialized Areas: Biomedical AI, Computer Vision, Machine Learning
⭐️ Long-term goal: to pursue advanced research in biomedical AI and develop trustworthy, explainable clinical decision support tools that can improve healthcare accessibility worldwide.