🚀 Researcher and developer passionate about AI, Federated Learning, Quantum-Inspired Optimization, and Satellite Networking.
I explore how Artificial Intelligence + Quantum-Inspired Algorithms can transform space–air–ground integrated networks (SAGINs) and future communication systems.
🌍 Based in Da Nang, Vietnam
🔗 Website: phuchaodo.coregenaihub.com
🐦 Twitter: @haodophuc
- Federated Learning in GEO/SAGIN Networks
- Quantum-Inspired Optimization (QIO) for resource management
- RIS-aided Communications
- Spatio-Temporal Graph Neural Networks (ST-GNNs)
- Latency minimization in large-scale networks
- 🔹 Q-FedSatSim — Federated Learning simulation over satellite networks with latency modeling.
- 🔹 Q-RISControl — Quantum-inspired AI control for Reconfigurable Intelligent Surfaces (RIS).
- 🔹 Quantum-Scheduler — Scheduler using hybrid quantum-classical optimization for SAGINs.
- 🔹 MultiModal-LatNet — Multi-modal data transmission with ST-GNN-based compression.
- 🔹 learning-simulation — AI/ML sandbox for simulation experiments.
- 🔹 learn-FL — Federated Learning fundamentals with clean Python implementations.
- 🦈 Pull Shark (active open-source contributor)
- ❄️ Arctic Code Vault Contributor (part of GitHub’s archival project)
💡 I’m open to collaborations in AI, quantum-inspired optimization, and satellite networking research.
If you’d like to contribute:
- Fork a repository
- Create a feature branch
- Push changes and open a Pull Request
✨ Thanks for visiting my profile! Feel free to explore the repositories, raise issues, or connect with me for research collaboration.