Information Technology student with hands-on experience building backend applications, REST APIs, real-time systems, machine learning solutions, and RAG-based chatbots using Java, Python, FastAPI, Flask, and SQL.
EduSkills & APSSDC
Apr 2025 – Jun 2025
Developed a content-based Movie Recommendation System using Python, TF-IDF, and cosine similarity. Applied text preprocessing, tokenization, and normalization to movie metadata, evaluated recommendations, and deployed the application through Streamlit with an integrated movie-poster API.
YES Club
Led social impact initiatives and volunteer-driven events.
Open Forge Club
Managed and coordinated tech-focused events.
AI Build Club
Contributed to AI research and development activities.
Bachelor of Technology, Information Technology
2022 – 2026
CGPA: 8.5/10
Intermediate, MPC
2020 – 2022
Percentage: 94%
SSC
2020
Percentage: 95%
Engineered a real-time traffic management system using YOLOv8, DeepSORT, and OpenCV for ROI-based vehicle detection, tracking, and adaptive signal control. Built a Central Coordinator Agent for congestion analysis, emergency vehicle detection, speed estimation, pollution estimation, and traffic violation detection. Implemented a Flask backend with SQLite, live video streaming, and a traffic analytics chatbot.
Architected a Retrieval-Augmented Generation chatbot using Pinecone and Gemini/OpenAI. Implemented document ingestion, chunking, embedding, semantic retrieval, and a Flask REST API with prompt-engineered system messages for safe responses.
Designed a Whole-Body Vibration analysis system using a Conv1D-BiLSTM model to predict safe speed recommendations from real-time vibration sensor data in accordance with ISO 2631-1. Built a FastAPI backend with JWT authentication and REST endpoints, using Firebase for real-time storage.
Delivered a FastAPI restaurant search backend using the Zomato dataset and PostgreSQL, with REST APIs, OAuth2/JWT authentication, pagination, and 5 km radius-based location filtering. Integrated the Gemini API for image-based restaurant query understanding.