I sit at the crossroads of biomedical engineering, healthcare AI, and business analytics — translating complex clinical and operational challenges into intelligent, scalable solutions.
Biomedical engineer focused on healthcare technologies, medical devices, medical imaging, healthcare AI, data analytics, and decision support systems. My background combines technical problem solving, project coordination, and healthcare-oriented analysis to support practical and data-informed solutions for clinical and operational environments.
Designing and deploying machine learning and deep learning models — from CNN-based medical image classification to predictive clinical analytics — to support smarter, faster healthcare decisions.
Transforming raw clinical and operational data into actionable insights through advanced analytics, risk modeling, and interactive dashboards that empower healthcare professionals.
Applying biomedical engineering principles to evaluate, develop, and optimize medical technologies — bridging technical precision with real-world clinical needs.
Integrating business analytics with healthcare operations to monitor KPIs, improve efficiency, and drive data-informed decisions across clinical and organizational environments.
An interactive healthcare analytics dashboard integrating operational KPIs, patient risk indicators, data visualization, and decision support metrics for hospital management.
Jumb!
A CNN-based medical imaging project using MRI datasets from ADNI and OASIS to classify Alzheimer’s disease stages. Includes preprocessing, augmentation, model training, and performance evaluation.
Building the future of AI-driven systems. Let’s connect on new opportunities.