Prasanna Kumar

Developed an AI forecasting engine for EV charging demand prediction using Python and Facebook Prophet on real operational datasets, improving forecasting accuracy by ~20% over baseline models. Built modular, cloud-ready API architecture and collaborated in Agile sprints with Git-based version control and technical documentation.

Built RESTful APIs using Java and Spring Boot to support backend business logic for full-stack applications. Integrated React and MySQL with secure API endpoints (CRUD and request validation), managed Git version control, and deployed/tested in cloud-based environments.

Analyzed 10,000+ structured records using Python and SQL to build and evaluate 5+ supervised machine learning models. Improved prediction accuracy by 18% through data preprocessing, feature engineering, and iterative hyperparameter optimization, while streamlining data processing pipelines and presenting findings to stakeholders.

Developed and configured enterprise CRM workflows using Apex and Lightning Web Components, integrating 3+ REST APIs to automate business processes. Reduced issue resolution time by 25% through debugging and configuration optimization and supported Agile sprint execution with documented use cases and client-facing technical discussions.

Pursuing an M.Tech in Cloud Computing (AI & Data Science), covering machine learning, deep learning, NLP, cloud architecture, and database management.

Completed a B.Tech in Information Technology with coursework in operating system principles, object-oriented programming, DBMS, computer vision, and artificial intelligence.