Hamid 279

I’m an aspiring AI / Machine Learning Engineer with hands-on experience in computer vision and deep learning. I build and optimize models using CNNs, Transformers, YOLO, GANs, and diffusion models, with a strong focus on performance and scalable deployment.

As an Artificial Intelligence Intern at Xylvanthrex Labs (Remote), I contributed to computer vision deep learning work using CNNs and Transformers. I implemented GANs and diffusion models to generate and enhance datasets, then deployed end-to-end ML pipelines using FastAPI and containerized solutions for integration with real-world data systems.

Before and alongside my ML work, I’ve gained practical reliability and security experience as an IT Production Support Engineer (Part-Time) and Information Technology Officer. I managed server uptime, performed system health checks, and executed backup and disaster recovery strategies, while supporting IT security operations such as incident response and system hardening with Fortinet firewalls and Trend Micro endpoint security.

My technical projects reflect how I think and build: my Final Year Project, “Potato Plant Disease Detection Using Deep Learning,” achieved 90–95% accuracy using preprocessing, augmentation, and hyperparameter tuning. I’ve also developed Handgun Detection using YOLO (with dataset annotation/preprocessing in Roboflow) and built image classification and synthetic image generation pipelines to support downstream machine learning tasks.