I build AI workflows demonstrating Python, data analytics, and automation skills that drive real buisiness leverage.
While improving my technical sckills as a PMP-Certified Project Manager I discovered passion for orchestrating AI workflows combined with scripts to solve productivity problems. My solutions save resources and bring x10 gains to those who use them due to meticulous requirements gathering and elicitation and transforming them into working solutions approved by the clients.
I orchestrate complex AI R&D workflows at the theory construction level—working with deep subject-matter experts while staying general, strategic, and agile. My strength is navigating oblique problems where vertical depth meets horizontal integration.
Current focus:
- Multi-agent AI orchestration for mathematical physics research
- Computational validation of theoretical frameworks
- Fractional Laplacian on Curved Manifolds: Heat kernel expansions with curvature corrections
- Surjection-to-QEC Framework: Group theory meets quantum error correction
- 432-Group Structure: Discrete cosmology and (maybe) baryon asymmetry hypotheses
- Complexity-Vector: No-go theorem proving scalar impossibility in multi-pillar complexity measures
- Omega Mod M: Number theory meets computational verification—Selberg-Delange law for prime omega functions (when I was fascinated with primes and ternary computing)
These repositories demonstrate end-to-end research workflows: theory design → computational implementation → experimental validation → data visualization → publication preparation.
Skills showcased: Python · NumPy · SciPy · PyTorch · Multi-agent AI workflows · GAP · LaTeX · Git · Research design · Statistical validation · TDD protocols
Background: Master degree in administration - turned AI project manager.
Learning to code is a lot more interesting when you have research questions in mind. 🚀