M.Sc. in Computer Engineering specializing in Deep Learning, CNNs, and Computer Vision applied to biomedical imaging — advancing AI-powered cancer detection and clinical diagnostics.
I am a Computer Engineer, researcher, and innovator with a Master's degree in Computer Engineering, specializing in Deep Learning, Convolutional Neural Networks (CNN), and Computer Vision. My passion lies in integrating artificial intelligence with biomedical imaging to develop cutting-edge solutions for critical healthcare challenges. Through years of academic study and hands-on research, I have focused extensively on the early and accurate detection of cancers—particularly breast cancer—by leveraging state-of-the-art techniques in AI and image analysis.
My work involves designing, optimizing, and implementing advanced AI pipelines for the automated detection, segmentation, and classification of cancerous lesions, aiming to support clinicians in making faster, more reliable diagnoses. I am adept at working with diverse medical imaging modalities including mammography, ultrasound, X-ray, and histopathology, and have developed robust models validated on large, annotated datasets.
In addition to research, I am deeply interested in the practical translation of AI models into clinical environments, emphasizing interpretability, reproducibility, and collaboration with multidisciplinary teams. My vision is to advance medical imaging and healthcare analytics by combining technical excellence with a dedication to real-world impact and innovation, contributing to improved patient outcomes and the next generation of intelligent healthcare systems.