Projects

Independently developed an interactive, user-defined shell in C, featuring support for pipelining, signal handling, and I/O redirection. Source Code.

Developed a full-stack application to remotely control the rotation speed of a DC motor and monitor live feed from the motor’s axis, integrated with oneM2M.

Contributed to backend development, oneM2M integration, and hardware assembly through soldering.

Independently developed a MERN stack website enabling vendors to take online orders and view order statistics with data visualizations.

Implemented features for users to explore food options through feedback and reviews from other customers. Dockerised the application. Source Code

Independently classified the MNIST dataset using various classical machine learning and deep learning methods under the supervision of a professor, gaining insights into fine-tuning neural networks while working with TensorFlow, PyTorch, and Scikit-learn. Source Code

Achieved a classfication accuracy of 99.6%.

Independently developed a predictive model using PyTorch, Pandas, and NumPy to assess depression risk based on music listening history, achieving a Mean Percentage Error of 4% through effective model design and fine-tuning. Source Code

Developed a personalized video recommendation system using Java, Springboot, and Apache Kafka, leveraging microservices architecture and RESTful APIs.

Led frontend development (React, Redux) and coordinated backend integration, applying strong analytical and problem-solving skills, and effectively managing project timelines. Source Code.