Quantum Computational Physics PhD who likes to code, build, and understand things from first principles.
I move comfortably between theory, computation, and real-world implementation — from many-body Hamiltonians to production-ready ML pipelines.
💡 You can read my latest research articles
👉 https://scholar.google.com/citations?user=nBuc_38AAAAJ&hl=es&authuser=1
I work at the intersection of:
- 🤖 Generative AI & LLM applications
- 🧩 Scientific Machine Learning
- 📊 Data-driven modeling
- ⚡ High-performance computing
- 🔬 Computational physics workflows
I’m especially interested in:
- Retrieval-Augmented Generation (RAG) systems
- LLM evaluation & alignment
- AI for scientific discovery
- Agent-based systems
- Multimodal models
- Scalable ML infrastructure
Here you will find code written in:
- 💝 Julia
- 🐍 Python
- 💾 FORTRAN
And increasingly:
- PyTorch
- Transformers (Hugging Face)
- LangChain / LLM orchestration tools
- Vector databases
- CUDA & parallel computing
Building and experimenting with:
- LLM-powered applications
- RAG pipelines
- Scientific AI assistants
- Evaluation frameworks for generative systems
- AI tools that augment research & reasoning
- Research-grade computational physics projects
- Machine learning experiments
- GenAI prototypes
- Clean, reproducible scientific workflows
- Occasional over-engineered side projects
If you're building in:
- AI / GenAI
- Deep Tech
- Scientific ML
- Research-driven startups
I'd love to collaborate.
⚡ From quantum many-body systems to generative models — I care about structure, rigor, and building systems that actually work.