class AIResearcher:
def __init__(self):
self.name = "Yasa"
self.role = "AI Researcher & Deep Learning Engineer"
self.education = "Computer Engineering"
self.certifications = ["CS50x", "CS50p", "CS50 AI"]
self.passions = [
"🏥 Medical AI & Healthcare Innovation",
"🧠 Neural Networks & Deep Learning",
"🤖 Intelligent Automation Systems",
"👁️ Computer Vision & NLP",
"🔬 Transfer Learning & Transformers"
]
self.current_focus = "Building AI that enhances human life"🎯 Mission: Bridging the gap between cutting-edge AI research and real-world applications that make a meaningful impact on healthcare and society.
| 🎯 Project | 📋 Description | 🛠️ Tech Stack | 📈 Status |
|---|---|---|---|
| 🏥 Medical AI Diagnostic | Deep learning for medical image analysis & disease detection | PyTorch • TensorFlow • OpenCV • ResNet | 🟢 Active |
| 🤖 AI Automation Platform | Intelligent data processing & cataloging system | Streamlit • FastAPI • n8n • AI Agents | 🟢 Active |
| 🧠 Neural Architecture Lab | Custom architectures & transfer learning experiments | PyTorch • Transformers • Hugging Face | 🟢 Active |
| 📚 RAG Knowledge System | Advanced retrieval-augmented generation | LangChain • Vector DB • LLMs • Embeddings | 🟡 Research |
| 🔄 MLOps Pipeline | End-to-end ML with automated deployment | Docker • Kubernetes • MLflow • CI/CD | 🟡 In Progress |