Sumit Kesarwani

Architected and deployed 20+ APIs and full-stack features using React.js, Node.js, Express.js, and MongoDB; secured 5+ modules with JWT authentication, RBAC, and 3 third-party API integrations. Cut page load times by 40% via Redis caching, database indexing, and lazy loading; shipped 15+ reusable React components, lowering code duplication across the team.

Built and fine-tuned machine learning models using Python, TensorFlow, and Scikit-learn, improving prediction accuracy on a research dataset. Designed data preprocessing and feature engineering pipelines for large-scale datasets; collaborated with graduate researchers to evaluate model performance for an applied AI research initiative.

Developed 10+ RESTful APIs using Node.js, Express.js, MongoDB, and Firebase; cut average query execution time by 30–50% via multi-field indexing and query tuning. Fortified 3 backend security layers — JWT authentication, role-based middleware, and server-side caching — maintaining a 100% incident-free post-deployment record.

Engineered and shipped 15+ UI components in React.js and Tailwind CSS, improving conversion metrics across 3 live landing pages. Overhauled 3+ CTA workflows, decreasing funnel drop-off and lifting session engagement; integrated Supabase for data sync and auth, removing 2+ redundant API layers.

Grade: 8.3 / 10.0

Pursuing a Bachelor of Technology in Computer Science and Engineering with an SGPA of 8.3/10.0.