Designed and developed a full-stack gamified donation platform using React, TypeScript, Flask, and MongoDB, facilitating seamless connections between donors and receivers engineered with a dynamic leaderboard system to gamify user engagement. Integrated a Gemini API-driven chatbot to improve user support, usability, and real-time assistance for donors and receivers

Developed a command-line banking system in C++ with user authentication and file-based storage, enabling secure account access and persistent transaction management. Implemented balance inquiry, deposits, withdrawals, and transfers, incorporating input validation, transaction logic, and error handling to ensure secure processing and enforce operational limits

Social media platforms like Twitter, Facebook, and Instagram reveal insights into users' mental health due to the anonymity of online interactions. This project examines the effectiveness of TF-IDF and Bag-of-Words (BoW) for stress detection in textual data. Various machine learning algorithms and deep learning models—SVM, Random Forest, Logistic Regression, Naive Bayes, RNN, LSTM, RoBERTa, and BERT embeddings are evaluated using datasets from Reddit and Twitter. The project aims to optimize stress detection systems by assessing how TF-IDF and BoW impact classifier performance.

Conceptualized and implemented a solution using the MobileNetV2 CNN model to generate synthetic images for early-stage diagnosis of four neurodegenerative diseases, and co-authored a paper on this solution, which was accepted at the 8th IEEE International Conference for Convergence of Technology 2023(ISSN: 979-8-3503-3401-2).

Devised a solution to predict the modalities like DNA, RNA, and Proteins at single-cell level using Neural Networks. Pre-processed the huge data using SVD dimensionality reduction technique and then using gelu activation function for dense neural layers predicted the covariance of modalities, offering valuable insights for diagnosing various carcinogenic diseases.

Proposed an algorithm in Solidity language for the simplified traceability of drug and other medicinal products in the supply chain. Authored a chapter for the simplified traceability of drug and other medicinal products in the supply chain in the book titled “Unleashing Potentials of Blockchain Technology for Healthcare Industries” published by Elsevier with Scopus index and ISBN: 978-0-323-99481-1