Why AI & ML?

Artificial Intelligence and Machine Learning allow me to apply data-driven insights to real-world problems. From building intelligent agents to deploying production-ready models, this field merges my passion for logic, automation, and impact-driven software.

Traffic Congestion Prediction

Built a big data pipeline using PySpark and Random Forests to predict traffic congestion using 94M+ rows of NYC traffic speed data. Deployed a REST API for real-time inference integrated with ELK stack for visualization and monitoring.

RAG-Based Q&A System

Developed a Retrieval-Augmented Generation (RAG) system using OpenAI APIs and FAISS vector search. Integrated with a Flask API to answer domain-specific queries by retrieving and synthesizing relevant knowledge from custom documents.

E-Commerce Price Prediction

Trained regression models using product metadata to forecast future prices of items on an e-commerce platform. Performed extensive EDA and feature engineering to improve prediction accuracy and interpretability.

Other Projects

Other explorations include facial attribute classification using CNNs, CVAE-based image generation, and dynamic difficulty AI for games. I continue to experiment with generative models, agents, and real-world data applications. Explore more on GitHub below.