Mariska Mascarenhas

Designed and developed an AI-based website generation platform leveraging Qwen 2.5 7B open-source LLM for automated business website creation. Implemented dynamic content generation, AI logo generation, and prompt engineering to improve content relevance and website quality.

Developed an end-to-end Retrieval-Augmented Generation (RAG) system with vector database solutions and OpenAI embeddings for semantic search across PDF documents, including OCR-enabled processing. Integrated GPT-4 for content generation and GPT-4o-mini for contextual question-answering with source citations, and built a conversational AI interface using Meta Cloud API for WhatsApp.

Designed and developed a Retrieval-Augmented Generation (RAG) system for answering natural language questions on financial datasets. Implemented semantic search using SentenceTransformers and FAISS, integrated OpenRouter LLM API, and built a Flask-based web interface.

Grade: 9.37 CGPA

Pursued a Bachelor of Science Honours in Computer Science with a focus on Artificial Intelligence and Machine Learning, achieving a CGPA of 9.37.

Completed Higher Secondary Education (12th) with a focus on Commerce, Arts, and Science.

Earned the Google Data Analytics Professional Certificate, offered by Google.

Earned certifications in Deep Learning with Python, MySQL Basics, OpenCV, and NumPy.

Completed CS50's Introduction to Programming with Python via edX.

Completed the Deloitte Australia Data Analytics Job Simulation.