Subashini S

I am an AI and Machine Learning graduate student with hands-on experience building end-to-end ML systems using Python, TensorFlow, PyTorch, and Scikit-learn. I focus on practical applications in computer vision and NLP and have completed internships that emphasized real-time data streaming and analytics.

During a software development internship I built a multilingual audio review platform with transcription, translation, speech synthesis, and WebSocket-based live audio streaming. As a data analyst intern I performed statistical analysis and designed interactive dashboards to support strategic planning.

My project work includes CNN-based fetal brain MRI classification (comparing SqueezeNet and DenseNet), a skin-type cosmetics classifier with 89% accuracy using logistic regression and cross-validation, and a MERN-stack e-commerce app with performance improvements from API optimization.

I bring a strong foundation in software development (MERN, Flask, Django), deployment experience (model serving, WebSocket integration, Docker), and a collaborative mindset; I am open to relocation and eager to contribute to AI-driven teams building impactful products.