Alessio Borgi

PhD Researcher in Graph Neural Networks & Generative AI
Sapienza University of Rome 🇮🇹 · University of Cambridge 🇬🇧

👨🏻‍💻 About

Education

• 🎓 PhD in Graph Neural Networks & Generative AI
• 🤖 Master of Engineering in Artificial Intelligence & Robotics
• 💻 Bachelor of Engineering in Applied Computer Science & AI

Research Interests

• Graph Neural Networks (GNNs) & geometric deep learning
• Topological Deep Learning & persistent homology
• Diffusion Models & generative AI
• Robot learning & embodied AI

Applications

• 🚀 Robotics & autonomous systems
• 👁️ Computer Vision & 3D understanding
• 🧬 Biomedical AI & scientific computing

📚 ML Blog Library

Comprehensive technical blog series with interactive posts, mathematical foundations, and paper figures:

• Book I: Transformers — Architecture, attention mechanisms, and applications
• Book II: Graph Neural Networks — Message passing, aggregation, and graph learning
• Book III: Sheaf Networks — Differential geometry and cellular learning
• Book IV: Topological Deep Learning — Persistent homology, TDA, and topological methods
• Book V: Reinforcement Learning — MDPs, value-based, policy-gradient, and applications
• Book VI: Robotics — Perception, control, manipulation, and sim-to-real transfer

🛠 Tech Stack

Languages & ML Frameworks

Robotics, DevOps & Tools

🤝 Collaboration

I’m passionate about collaborative research and open science. I actively contribute to:

• Peer Review — Reviewer for major ML/AI conferences (NeurIPS, ICML, ICLR, CVPR)
• Open Source — Active contributor to GNN toolkits and deep learning libraries
• Mentoring — Supporting students in geometric deep learning and robotics research
• Research Partnerships — Always open to collaborative projects in GNNs, topological methods, robotics, and generative AI

If you’re interested in:

• Collaborating on research or publications
• Contributing to open-source projects
• Discussing ideas in geometric deep learning, robotics, or generative AI
• Academic partnerships or internships

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