I am a Computer Science undergraduate and Software Engineering Apprentice focused on building intelligent software systems at the intersection of Artificial Intelligence, Machine Learning, Cloud Computing, and Software Engineering.
My areas of interest include Applied Machine Learning, Generative AI, Retrieval-Augmented Generation (RAG), Computer Vision, IoT Analytics, and Cloud-Native Applications, with an emphasis on designing scalable and production-oriented solutions.
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Repository:
An explainable plagiarism detection framework combining classical string matching algorithms, structural similarity analysis, and source intelligence to identify different forms of plagiarism without dependency on external AI APIs.
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Repository:
Contributed to the machine learning and analytics components of an IoT-based healthcare monitoring platform focused on detecting and analysing wandering behaviour.
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Status: In Progress
Developing an enterprise AI assistant that converts infrastructure repositories, Ansible roles, and operational documentation into structured knowledge representations for semantic search and LLM-powered assistance.
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Repository:
Developed supervised machine learning models for predicting cloud cover using atmospheric and environmental parameters.
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- Large Language Models and Generative AI
- Retrieval-Augmented Generation Systems
- Azure AI and Cloud Engineering
- Machine Learning Systems
- IoT Data Analytics
- Backend and Distributed Systems
