Projects

A comprehensive multimodal approach to gold price forecasting using state-of-the-art deep learning architectures. By leveraging multiple economic indicators and advanced time series models, we achieve robust predictions for gold futures prices.

A comprehensive deep learning system for detecting violence and aggression using multiple modalities: audio, textual, facial expressions, and body pose.

Interactive AI demos featuring real-time image classification, object detection, and camera integration. Built with TensorFlow.js for client-side ML inference.

Modern portfolio with AI chat assistant, interactive resume, and dynamic project showcases. Features real-time AI responses about my background and work.

Advanced neural network system that learns music preferences based on weather patterns using Deep Q-Network reinforcement learning. Features real-time neural network visualization and C++ engine compiled to WebAssembly for high performance.

Python application that scrapes and extracts data from the California DMV website to calculate the frequency of autonomous vehicle accidents in 2023 by company. Provides insights into AV safety trends and regulatory compliance.

Motion detection library designed to detect movement and changes in images. Applied to calculate water level changes at California lakes and reservoirs, providing environmental monitoring capabilities.

Advanced Model Context Protocol (MCP) integration project currently in development. This project will demonstrate seamless AI model communication and context sharing capabilities.