Computer Vision Specialist
Master's student at ASU with a focus on computer vision and machine learning. Passionate about applying AI and data science to humanitarian challenges, using self-supervised learning and deep learning to drive social good.
- Languages: Python, C++, Java
- Frameworks: PyTorch, torchvision, Pillow, OpenCV, scikit-learn, Hugging Face
- Tools: Git, Jupyter, Linux, VS Code, Conda, Docker
- Deep Learning: Transformers (ViTs), ConvNets, Self-Supervised Learning, Image Segmentation, Object-Detection, Classification, Unsupervised Learning
- Humanitarian AI: Computer vision & deep learning for social impact.
- AI-Driven Healthcare: Intelligent diagnostics & accessibility.
- Ethical AI & Detection: Combating misinformation through image analysis.
- Self-Supervised Learning
- Mineral Segmentation: Developing a self-supervised segmentation method for complex mineral segmentation.
- Aegis: Improved detection of AI-generated images by 7% using Swin-Transformer V2
- Languages: English (Fluent), Greek (Conversational)
- Interests: Humanitarian AI, Computer Vision, Astronomy, Music
Open to collaborations on AI-driven social impact projects. Connect on LinkedIn or via email!