Iβm Zeinab Rahbar β a researcher and developer passionate about multimodal learning, latent graph learning, and Graph Neural Networks (GNNs).
πΌ What I Work On
- Researching multimodal learning and latent graph learning for complex data integration.
- Applying multimodal GNNs to VQA (Visual Question Answering) and other cross-modal tasks.
- Working on LLM-powered systems with automation workflows using Dify and n8n for content generation.
- Exploring Geometric Deep Learning to model complex relationships across data modalities.
π§ Projects
πΉ Multimodal GNN Research β Integrating text, image, and graph data for VQA and predictive modeling.
πΉ LLM Automation Workflows β Orchestrating content generation pipelines using Dify and n8n.
πΉ Latent Graph Learning Projects β Learning hidden structures and relationships in multimodal data.
π§° Tech Stack
- Languages: Python, LaTeX
- Databases: PostgreSQL
- Machine Learning: PyTorch, TensorFlow, PyTorch Geometric, DGL, Graph Neural Networks
- Workflow Automation: Dify, n8n
- Tools & Frameworks: Docker, LangChain, llama-index
π Open to Collaborate
Iβm open to collaborations in multimodal learning, geometric deep learning, latent graph learning, and LLM research.
π« Get in Touch
- Telegram: @Zeinabrahbar2000
- LinkedIn: Zeinab Rahbar
β‘ Fun Fact / Motto: Iβm proud to rise after every challenge β resilience is my superpower!
