Projects
Research & Development Portfolio
My project portfolio showcases practical applications of my research in AI/ML, 6G networks, and smart systems. These projects demonstrate how theoretical concepts can be implemented to solve real-world problems and advance technology in telecommunications and intelligent systems.
Multi-Agent Energy Management System
Developed a distributed energy management simulation framework modeling multiple household HVAC systems and storage units. The system employs reinforcement learning algorithms to optimize energy distribution across the network while maintaining temperature constraints, featuring price-based coordination mechanisms between local agents and a central orchestrator for efficient grid interaction.
COMIX: Conflict Management in O-RAN
Developed a generalized conflict management framework for multi-channel power control in O-RAN xApps. The project implements DRL-based solutions for optimizing network power control and energy efficiency, featuring an evaluation framework using Network Digital Twin (NDT) that achieved significant energy savings.
SnakeAI-DQN
This project implements a Deep Q-Network (DQN) to train an AI agent to play the classic Snake game. The agent learns to play the game by interacting with the environment, observing the state, and learning from rewards and penalties. The implementation uses PyTorch for the neural network, Gym for the environment interface, and Pygame for rendering the game.
Heart Disease Prediction with Machine Learning
Developed and analyzed heart disease prediction models using Python and R, interpreting decision trees for actionable insights. Integrated Prolog for knowledge representation and created a Java interface for user-friendly predictions.
UsedCarsAnalysis
This repository showcases an extensive exploration of used car prices using the detailed 'autos.csv' dataset. Through comprehensive data analysis, it investigates the impact of car features such as make, model, year, mileage, and price, providing valuable insights for both buyers and sellers in the used car market.
Naive-Bayes-Spam-Classifier
A Python-based machine learning project for identifying and filtering spam emails using a Naive Bayes Classifier. The classifier is trained on a labeled dataset to distinguish between spam and legitimate emails, achieving high accuracy and precision in predictions.
Data-Analysis-with-R
Explore Data Analysis for key insights from three pivotal papers on R-based data analysis techniques. This project delves into statistical methods, data visualization, and model building using R, providing a comprehensive understanding of advanced data analysis practices.
Contact
I am receptive to discussing new research and development initiatives related to AI/ML, 6G networks, and smart systems. Should you have any questions about my projects or wish to explore a collaboration, please feel free to get in touch.