Projects

Predicting QoS for Vehicular Networks with Machine Learning techniques

Developed a predictive model utilizing feature engineering and XGBoost regression to forecast Quality of Service (QoS) metrics in vehicular networks. Aids in optimizing network performance for connected vehicles in eventual smart cities. 

Using GANs to generate CBOE volatility index values

Employed Generative Adversarial Networks (GANs) to model and generate synthetic data replicating the Chicago Board Options Exchange (CBOE) Volatility Index (VIX). This project provides insights into financial market simulations and risk assessment!

PCAP Vulnerability Analyzer

A simple service to analyze flow-level network traffic and get AI-powered vulnerability explanations. The analyzer flags suspicious encrypted traffic, classifies flow types, and helps identify potential security risks.

"Bachman"

Blended music theory and retro gaming! Bachman is a playable Pac-Man-style game designed to teach and reinforce music note recognition. Built in Lua using LÖVE2D on macOS and hosted on Firebase.

Real-time Parkinson's Tremor detection system

Implemented a real-time tremormonitoring system using an STM32 microcontroller and gyroscopic sensors to detect and classify Parkinsonian tremors. The system offers immediate feedback and logs data for continuous patient monitoring.

Simulated RISC-V Pipelined Processor

Register-based simulation of a 5-stage pipelined RISC-V processor, focusing on instruction throughput optimization and hazard mitigation techniques. This project serves as an educational tool for understanding CPU architecture and pipeline processing.