B.E. student specializing in Artificial Intelligence and Machine Learning at Ramaiah Institute of Technology, demonstrating strong academic performance and technical proficiency. Skilled in Python, C, C++, JavaScript, and React, with expertise in Data Structures, Algorithms, and Web Development. Engaged in practical AI and ML projects, enhancing hands-on experience. Achieved recognition as a top coder on Coding Ninjas for exceptional problem-solving skills.
Buy Buddy AI (e-commerce chatbot)
Tech stack: Python, Streamlit, Flask, React, Tailwind CSS, ChromaDB, Google Gemini, Whisper, gTTS.
Built an intelligent voice- and text-enabled e-commerce chatbot that recommends products using GenAI and vector-based semantic search.
Implemented a custom RAG (Retrieval-Augmented Generation) pipeline with ChromaDB and Google Gemini to generate personalized product suggestions based on user queries.
NutriNova-Diet Recommendation and Management System:
ReactJS, MongoDB, ExpressJS, NodeJS, Tailwind, LangChain, built a comprehensive diet recommendation and management system using the MERN stack, implemented user authentication and authorization, ensuring secure access to personalized dietary plans and features, developed and integrated a chatbot using LangChain to provide users with real-time dietary suggestions and nutritional information.
music recommendation system based on facial emotion:
self-learning project, CNN, ReactJS, NodeJS, MongoDB, Tailwind, Flask, used the FER-2013 dataset to build a strong deep learning model that can read a user’s facial expressions to figure out how they are feeling (happy, sad, etc) and suggest songs that fit that mood., Used Flask to deploy the model and ReactJS to make the frontend. ExpressJS and MongoDB were used to make a proper user login system.