Highly motivated Computer Engineering student with a strong foundation in software development and a dedicated research interest in Machine Learning, particularly focusing on Continual Learning, Decentralized Systems, and efficient AI deployment on resource-constrained devices (Edge AI). Proven ability to implement complex algorithms, conduct experiments, and translate theoretical concepts into practical applications, demonstrated through projects involving autoencoders on microcontrollers and industry experience in full-stack development. Eager to contribute to cutting edge research in adaptive and distributed AI systems as a Visiting Researcher at the Pervasive AI Lab.
Worked on full-stack development using the MEAN stack. Led deployment using Docker and GitLab CI/CD pipelines. Built responsive UIs with Angular and contributed to backend services using Node.js and Express. Focused on scalable solutions and clean architecture practices.
Digital Explorers is a knowledge exchange initiative between 2 buzzing ICT, offering.
A machine learning project using AutoEncoders for secure data compression and encryption, specifically designed for deployment on low-resource devices like ESP32 and Raspberry Pi.
A lightweight URL shortening backend system built with Node.js and Express. It generates short aliases for long URLs, supporting RESTful APIs for full CRUD operations.
A responsive and interactive charity web frontend built using nextt. Part of a team-based effort to build a full-stack app for managing care services.