Background: Post-graduate in Mathematics
Goal: Building intelligent systems
I specialize in bridging the gap between theoretical mathematics and real-world applications, using computational methods and ML to crack complex problems that exist at the intersection of:
- 🔢 Pure mathematical challenges
- 📊 Domain-specific analytical problems
- Python – my goto language
- Coq/Rocq – Learning
- Lean4 - Learning
- NumPy & Pandas
- Scikit-learn
- TensorFlow & PyTorch
- PyTorch
I'm currently deep in the mathematical trenches exploring:
-
Category Theory and Software foundations
Understanding how super intelligent systems can be built with foundations in Type theory -
Algorithmic Techniques in Group Theory
Uncovering computational patterns in algebraic structures -
🧠 Deep Neural Network Architectures
Understanding what makes networks tick (and converge)
Most of what I know came from late-night documentation deep-dives, countless Stack Overflow tabs.
My learning philosophy:
- 📚 Read, Do, Read, Do, Fail, Read, Do
I'm always excited to work on interesting problems, especially those involving:
- Automated Theorem Proving
- Superintelligent Systems
- Machine learning applications
- Computational methods for complex systems
- Analytics and data intelligence
Got a challenging project? I'm happy to learn, contribute, and help bring mathematical elegance to your codebase.