I'm a Computer Engineering student at NMIMS, Mumbai, interested in Machine Learning, Artificial Intelligence, and Generative AI.
I build end-to-end AI applications that combine machine learning models, LLMs, APIs, and modern software systems to solve practical problems. My interests include RAG systems, Agentic AI, NLP, predictive analytics, and AI-powered decision systems.
Currently focused on building and experimenting with Agentic AI and advanced LLM applications, with an emphasis on systems that can reason, retrieve information, interact with tools, and make decisions.
I'm also exploring RAG architectures, LLM evaluation, machine learning for real-world decision systems, and scalable AI applications using technologies such as FastAPI, React, Docker, PyTorch, and AWS.
Hugging Face Transformers • NLP • RAG • Recommendation Systems • Predictive Analytics
OpenAI APIs • Gemini APIs • LLM Evaluation • Prompt Engineering • Agentic AI
An AI-powered music recommendation system that detects emotions from voice and text input and recommends songs based on the user's mood.
Technologies: Python • Transformers • Streamlit • Spotify API
A retrieval-augmented generation system for document-based question answering and LLM evaluation.
The project evaluates different retrieval strategies and LLM configurations to study their impact on answer quality.
Technologies: Python • RAG • NLP • LLMs
Publication: IEEE WCSC 2026
An intelligent workload scheduling system that uses Reinforcement Learning to schedule computational workloads based on carbon intensity.
The system combines a Deep Q-Network (DQN) agent with carbon-intensity data to make more environmentally aware scheduling decisions.
Technologies: PyTorch • DQN • Reinforcement Learning • FastAPI • React
An end-to-end machine learning pipeline for predicting movie revenue using real-world datasets.
Implemented feature engineering, model comparison, hyperparameter tuning, and evaluation across multiple regression models.
Result: R² = 0.77
Publication: DACS 8.0 2025
📄 WCSC 2026 Multi-Document RAG System and LLM Evaluation
📄 DACS 8.0 2025 Box Office Revenue Prediction using Machine Learning
📄 OTCON 5.0 2026 Eco-Scheduler — Carbon-Aware AI Scheduling
Building intelligent systems with AI.