Projects

A Python package implementing multiple diffusion model variants, sampling strategies, and controllable generation techniques for image synthesis and manipulation.

A reinforcement learning system implementing both tabular methods (Q-Learning, SARSA) and deep learning approaches (DQN) with a focus on performance optimization and benchmarking.

A distributed data processing pipeline built with PySpark to extract, transform, and analyze large-scale social media datasets.

A browser game featuring four cognitive training modes (including three originals) that extend N-Back through spatial and temporal recall, and multi-target recognition challenges.

A modular corpus management system for sentiment analysis featuring intelligent caching, parallel processing, and dual-backend linguistic analysis.

A statistical analysis implementing PCA, LDA and Naive Bayes for classification and K-Means to identify groupings based on dietary habits, physical activity, and demographic variables.

A comprehensive benchmarking framework designed to evaluate the throughput, latency, and resource consumption of SQL and NoSQL database engines using multi-threaded synthetic data generation.

An encryption algorithm based on concentric regular polygons using trigonometric positioning, with optional layer-based secondary ciphers.