Designed and implemented a dynamic personal finance dashboard using React and Node.js, enabling users to track income, expenses, and savings with real-time data visualizations and customizable financial goals. • Developed and integrated secure RESTful APIs with Express, allowing seamless communication between the front-end and back-end, ensuring secure data exchange and optimal performance across the platform. • Utilized MongoDB for efficient storage of user financial data, providing fast data retrieval and ensuring data consistency with schema design and indexing strategies to handle growing user demands. • Implemented real-time data synchronization for live spending tracking and budget updates, leveraging WebSockets for seamless communication and ensuring users receive accurate updates without page reloads. • Deployed the system on AWS EC2 for scalable cloud infrastructure, used AWS S3 for secure file storage, and integrated load balancing, ensuring high availability, 99.9% uptime, and seamless user experience globally. • Scripted and maintained unit and integration tests using Jest and Mocha to ensure code reliability, while automating the deployment process with Jenkins and implementing CI/CD pipelines for rapid feature releases and continuous delivery.

Designed and built a management and admin console for an internal React-based application. This system utilizes AWS Lambda, S3, and DynamoDB, streamlining operations and enabling scalability, all while using fewer resources. Worked closely with stakeholders, ensuring their requirements were met, resulting in a 75% increase in overall efficiency. Our focus on high standards throughout the process has led to a product that not only meets expectations but exceeds them. This achievement showcases our commitment to innovation and excellence in every aspect of our work.

Designed and developed the front-end of the finance app using React, ensuring responsive UI/UX to provide a seamless user experience across devices. Integrated React Hooks and Context API for efficient state management. • Implemented back-end services using Node.js and Express, designing RESTful APIs for user authentication, transaction management, and data retrieval, ensuring scalability and high performance of financial data processing. • Utilized MongoDB for efficient data storage, modeling user financial data and transaction history while ensuring data consistency and security, meeting GDPR and privacy compliance standards. • Integrated third-party APIs for real-time transaction tracking, budgeting, and automated expense categorization, enabling users to manage and monitor their finances efficiently. Used Axios for smooth data flow between front-end and back-end. • Built a dynamic reporting module using Chart.js for generating financial summaries, monthly reports, and visual analytics, allowing users to track expenses and savings trends over time. • Employed JWT authentication for secure login and role-based access, ensuring user data privacy and safeguarding sensitive financial information, adhering to industry security best practices. • Conducted broad testing using Jest and Mocha for unit and integration tests, ensuring app stability. Set up CI/CD pipelines using Azure DevOps for automated testing, builds, and deployments to Azure App Services for smooth production releases.

Developed a versatile cross-platform application seamlessly operating on various devices. Powered by JavaScript, it leverages the MERN stack for robustness - MongoDB for data management, Express.js for API creation, React.js for dynamic UI, and Node.js for a swift backend. Adding to this, the Ionic Framework ensures a native-like experience across platforms. What sets this application apart is its recommendation engine, fortified with Natural Language Processing. This engine deciphers user-generated content, unveiling insights and sentiments to offer personalized suggestions. It's a fusion of technology and human understanding, promising an unmatched user experience. Welcome to a new standard in cross-platform applications.

Led a dedicated team of four in the development of a cutting-edge women's safety native application using the Ionic Framework. This innovative app serves as a crucial tool in assisting individuals during emergency situations by monitoring their pulse rate in real-time. Our project was driven by a strong sense of social responsibility, aiming to provide women with a reliable and accessible means of ensuring their safety. Through meticulous planning, collaborative efforts, and a deep understanding of both the Ionic Framework and pulse rate monitoring technology, we successfully created a powerful application that addresses a critical need in today's society. Our collective commitment to this cause has resulted in a solution that empowers individuals and promotes a safer environment for all.

Developed a system utilizing Convolutional Neural Networks (CNNs) to recognize various sign languages, aiming to facilitate communication for deaf and mute individuals. These CNNs, specialized deep learning models proficient in processing image data, underwent extensive training on a diverse dataset of annotated sign language gestures. Through this process, the network learned to discern unique features and patterns specific to each sign, allowing it to generalize its knowledge and effectively recognize a wide range of gestures.

Engineered a model using Python, OpenCV, TensorFlow, and Keras to monitor employee efficiency through face recognition and human tracking. This adaptable solution underwent thorough testing in diverse environments to guarantee its precision and dependability. By seamlessly integrating these cutting-edge technologies, the model not only accurately identifies employees but also offers real-time feedback on their performance, ultimately boosting operational efficiency across a range of work environments. This innovative tool has the potential to significantly optimize workforce productivity and streamline operations.