MASc. Candidate · Concordia University
Aspiring cybersecurity professional with academic training in computer science and information systems security. Completed a B.Sc. in Computer Science at North South University in 2024 and currently pursuing an MASc. at Concordia University. Brings hands-on experience in building web applications, mentoring students, and applying secure development practices to real-world problems.
I am an aspiring cybersecurity professional with a strong foundation in computer science and information systems security. I completed my B.Sc. in Computer Science at North South University in 2024, graduating with a research background in explainable AI and deep learning applied to healthcare.
I am currently pursuing an MASc. at Concordia University, where my research focuses on the intersection of cybersecurity and machine learning. I am interested in building trustworthy, interpretable AI systems and understanding how adversarial threats affect modern ML pipelines.
Beyond research, I enjoy mentoring students and translating complex technical concepts into accessible learning experiences—skills honed over two years as a Teaching Assistant at NSU.
Developed deep learning models (VGG16, VGG19) for brain MRI analysis, focusing on interpretability using SHAP, LRP, GRAD-CAM, and LIME. Improved transparency and trust in AI-based diagnostic decisions through explainable AI techniques. Collaborated with healthcare professionals to address real-world challenges in medical diagnostics.
Novel architecture designed to improve embedding quality and cluster tabular data effectively using self-supervised learning (SSL). The pipeline involves feature extraction, dimensionality reduction, and embedding enhancement via SSL frameworks, enabling more accurate and interpretable clustering outcomes.
Processes preprocessed multimodal data through convolutional layers for feature extraction, with final layers handling classification. Filter visualization reveals what patterns the network has learned, while sparsing improves efficiency by pruning less meaningful connections.
Whether you have a research collaboration in mind, a question about my work, or just want to connect, feel free to reach out.