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.