•Developed new features for Ultraviolet, a research data platform for storing & sharing academic outputs, improving functionalities•Utilized ReactJS and Jinja templates to build dynamic and user-friendly interfaces to improve user experience•Implemented extensive UI and Selenium End-to-End tests, attaining 80% coverage to ensure code quality & system reliability•Built a CI/CD pipeline with AWS EC2 & GitHub Actions to optimize testing & integration, elevating code integration by 15%•Led extensive dependency upgrades on customized components 3 years ago to latest upstream to align with latest release•Collaborated with team using Jira to track tasks, manage sprints, and prioritize features in an agile development environment

• Collaborated with lab members on enhancing Multi-path QUIC, congestion control and FEC strategies with Mininet• Executed comprehensive network performance evaluations of various FEC schemes, including XOR, Reed-Solomon (RS), Delay Sensitive, Adaptive, and Deep Learning based Adaptive FEC approaches

• Redesigned database schema for a job board website that provides application tracking platform for small business and utilized Django and PostgreSQL to build the backend, improving user management and application processes• Crafted a responsive analytical dashboard using HTML/CSS and Bootstrap5, improving website usability• Incorporated Chart.js to enhance the analytics dashboard with dynamic interactive visualization of candidate statistics• Integrated Stripe API and webhook into payment infrastructure, enabling subscription management and coupon redemption• Elevated website responsiveness with Celery and Redis for distributed task processing, and message brokerage

• Examined the correlation between 150+ students' code inefficiency patterns and their performance in computer science courses• Engineered a data collection and preprocessing pipeline using Bash scripts and Python unittest for performance evaluation, ensuring the anonymization and integrity of student coursework data for analysis• Utilized regression analysis and decision tree models to identify and evaluate code inefficiency patterns, quantifying their impact on student performance and uncovering actionable insights with Pandas and Scikit-Learn