About Me
Artificial Intelligence graduate with hands-on experience in Machine Learning, Deep Learning, Computer Vision, and Natural Language Processing. Enrolled in the AI.SPIRE Program to further develop industry-focused AI engi…
Artificial Intelligence graduate with hands-on experience in Machine Learning, Deep Learning, Computer Vision, and Natural Language Processing. Enrolled in the AI.SPIRE Program to further develop industry-focused AI engineering skills. Proficient in building AI solutions using PyTorch, Hugging Face Transformers, and modern ML frameworks through academic research, internships, and independent projects. Achieved an internship at Integrated Technology Group (ITG), where I contributed to an AI-powered identity document processing pipeline for automated data extraction. Developed a graduation project featuring an AI-driven interview practice platform integrating NLP, speech emotion recognition, and behavioral analysis to deliver automated performance feedback. Highly motivated and passionate about Artificial Intelligence, with a strong focus on Retrieval-Augmented Generation (RAG) systems and building real-world intelligent applications.
Experience
AI.SPIRE Trainee
<p>Achieved applied AI engineering projects covering Python, SQL, Machine Learning, NLP, and RAG, with multiple test-based submissions including perfect scores of 18/18 and 9/9 on automated test suites.</p><p> Delivered a sentiment classification pipeline and generated predictions for 1,033 app review samples, demonstrating end-to-end NLP delivery from raw text to inference output.</p><p> Analysed a student performance dataset of 2,000 records, identifying a 0.639 correlation between study hours and GPA; built an ETL pipeline processing 100 records that passed 3/3 validation tests.</p><p> Developed a PDF-based Retrieval-Augmented Generation (RAG) prototype: processed a 5-page document, split it into 11 searchable chunks, and indexed 384-dimensional embeddings using FAISS for semantic retrieval.</p>
AI Intern
<p>Designed and implemented an AI-powered pipeline to extract Machine Readable Zone (MRZ) data from passports and civil ID documents, integrated into a hotel guest-processing workflow — reducing manual data-entry time by an estimated 60%.</p><p> Applied OCR, Computer Vision, and NLP techniques to automate identity data extraction, improving document handling accuracy and overall processing efficiency.</p>