- 🎓 PhD student in Mathematics at CINVESTAV, working on Knot Theory, Graph Neural Networks, and Reinforcement Learning.
- 💡 Passionate about blending pure math with machine learning for scientific discovery and theoretical insight.
- 🎤 Regular contributor and speaker at international conferences (ICERM, IMSA, FinAI Summit).
- 📚 Explorer of abstract algebra, topology, and the limits of machine intelligence.
- Languages: Python, R, SQL, LaTeX
- ML/DL: PyTorch, TensorFlow, Scikit-learn, XGBoost
- Graphs: DGL, PyG, NetworkX
- Visualization: Plotly, Matplotlib, Seaborn
- Tools: Git, Docker, VSCode, Jupyter, Overleaf
- 🔗 KnotNet: Deep learning models to predict HOMFLY polynomials using Alexander & Jones invariants.
- 🧠 GNN Anomaly Detection: Graph Autoencoders for identifying outliers in electronic component markets.
- 🧩 Reinforcement Learning for Knot Simplification: PPO-based agent applying Reidemeister moves for diagram reduction.
